Vanderbilt University
Private University • US
Showing 73 courses from Vanderbilt
Prompt Engineering for ChatGPT - Vanderbilt University
Vanderbilt University (via Coursera)
Prompt Engineering for ChatGPT - Vanderbilt University is a comprehensive beginner-level resource offered by Vanderbilt University, focused on building practical skills in artificial intelligence and machine learning. Whether you're a complete beginner looking to start a new career or a professional aiming to upgrade your skills, this resource provides a thorough learning experience. This is a structured online course with a carefully designed curriculum. Each module builds on the previous one, creating a logical progression from fundamentals to advanced topics. The course typically includes video lectures, reading materials, hands-on exercises, quizzes, and sometimes peer-reviewed assignments. This structured approach ensures you don't miss any critical concepts and build a solid foundation. This resource covers topics essential for success in artificial intelligence and machine learning, including machine learning algorithms, deep learning, NLP, computer vision, and model deployment. The curriculum is structured to build your knowledge progressively — starting with foundational concepts and advancing to real-world applications. By the end, you should be able to: Use ChatGPT effectively for productivity and learning Master prompt engineering techniques Integrate ChatGPT into workflows via the OpenAI API Build custom GPTs and assistants Duration: Estimated duration: 10 hours of content, designed to be completed in 1-2 weeks at a comfortable pace. No prior experience is required. This course starts from the absolute basics and gradually builds up complexity. A computer with internet access is all you need to get started. This resource is designed for a wide audience: Students (B.Tech, BCA, MCA, BSc) looking to complement their academic learning with practical, industry-relevant skills Fresh graduates preparing for campus placements or off-campus interviews Working professionals looking to upskill, switch domains, or advance their careers Career changers transitioning from non-tech backgrounds into artificial intelligence and machine learning Freelancers wanting to add new services to their portfolio Self-learners passionate about artificial intelligence and machine learning and wanting structured guidance Pricing: This resource is completely free with no hidden charges. Completing this resource and building related skills can prepare you for roles such as ML Engineer, AI Engineer, Data Scientist, Research Scientist. Realistic salary bands in India (2025-2026), based on Naukri/AmbitionBox data: Freshers / 0-2 years: Rs 8-15 LPA Mid-level / 2-5 years: Rs 18-35 LPA Senior / 5+ years: Rs 40-80 LPA Actual offers vary heavily by city, company tier, and how strong your portfolio or interview performance is. Companies actively hiring in this space include Google, Microsoft, OpenAI, Indian AI startups, research labs. India is the second-largest AI talent pool globally, and the demand far exceeds supply. The Indian AI market is expected to reach $17 billion by 2027. Every major Indian tech company — from Infosys to Reliance to Jio — is investing heavily in AI capabilities. The emergence of generative AI has created entirely new job categories that didn't exist two years ago. ML engineers with LLM experience are commanding Rs 30-60 LPA even at early career stages. Vanderbilt University is a well-established platform trusted by millions of learners worldwide. This particular resource has been selected by our editorial team based on: Content quality — comprehensive coverage with clear explanations Practical focus — emphasis on hands-on skills over pure theory Student outcomes — positive reviews and career success stories Indian relevance — content applicable to the Indian job market and interview patterns Updated curriculum — material reflects current industry practices and tools We regularly review and update our recommendations to ensure they remain relevant and high-quality.
Prompt Engineering for ChatGPT - Vanderbilt University
Vanderbilt University (via Coursera)
Prompt Engineering for ChatGPT - Vanderbilt University is a comprehensive beginner-level resource offered by Vanderbilt University, focused on building practical skills in programming and data structures. Whether you're a complete beginner looking to start a new career or a professional aiming to upgrade your skills, this resource provides a thorough learning experience. This is a structured online course with a carefully designed curriculum. Each module builds on the previous one, creating a logical progression from fundamentals to advanced topics. The course typically includes video lectures, reading materials, hands-on exercises, quizzes, and sometimes peer-reviewed assignments. This structured approach ensures you don't miss any critical concepts and build a solid foundation. This resource covers topics essential for success in programming and data structures, including algorithms, data structures, system design, and coding interview patterns. The curriculum is structured to build your knowledge progressively — starting with foundational concepts and advancing to real-world applications. By the end, you should be able to: Use ChatGPT effectively for productivity and learning Master prompt engineering techniques Integrate ChatGPT into workflows via the OpenAI API Build custom GPTs and assistants Duration: Estimated duration: 8 hours of content, designed to be completed in 1-2 weeks at a comfortable pace. No prior experience is required. This course starts from the absolute basics and gradually builds up complexity. A computer with internet access is all you need to get started. This resource is designed for a wide audience: Students (B.Tech, BCA, MCA, BSc) looking to complement their academic learning with practical, industry-relevant skills Fresh graduates preparing for campus placements or off-campus interviews Working professionals looking to upskill, switch domains, or advance their careers Career changers transitioning from non-tech backgrounds into programming and data structures Freelancers wanting to add new services to their portfolio Self-learners passionate about programming and data structures and wanting structured guidance Pricing: This resource is completely free with no hidden charges. Completing this resource and building related skills can prepare you for roles such as Software Development Engineer (SDE), Software Engineer, Backend Developer. Realistic salary bands in India (2025-2026), based on Naukri/AmbitionBox data: Freshers / 0-2 years: Rs 6-12 LPA Mid-level / 2-5 years: Rs 15-30 LPA Senior / 5+ years: Rs 30-60 LPA Actual offers vary heavily by city, company tier, and how strong your portfolio or interview performance is. Companies actively hiring in this space include Google, Amazon, Microsoft, Flipkart, PhonePe, Atlassian. Strong programming and DSA skills are the 1 factor in clearing technical interviews at product companies. Companies like Google, Amazon, Microsoft, Flipkart, and PhonePe all use coding rounds as their primary hiring filter. The Indian tech interview landscape typically involves 2-3 DSA rounds, 1 system design round (for experienced roles), and 1-2 behavioral rounds. Candidates who have solved 200+ quality problems on platforms like LeetCode consistently report higher interview success rates. Vanderbilt University is a well-established platform trusted by millions of learners worldwide. This particular resource has been selected by our editorial team based on: Content quality — comprehensive coverage with clear explanations Practical focus — emphasis on hands-on skills over pure theory Student outcomes — positive reviews and career success stories Indian relevance — content applicable to the Indian job market and interview patterns Updated curriculum — material reflects current industry practices and tools We regularly review and update our recommendations to ensure they remain relevant and high-quality.
Introduction to Generative AI - Vanderbilt University
Vanderbilt University (via Coursera)
Introduction to Generative AI - Vanderbilt University is a comprehensive beginner-level resource offered by Vanderbilt University, focused on building practical skills in artificial intelligence and machine learning. Whether you're a complete beginner looking to start a new career or a professional aiming to upgrade your skills, this resource provides a thorough learning experience. This is a structured online course with a carefully designed curriculum. Each module builds on the previous one, creating a logical progression from fundamentals to advanced topics. The course typically includes video lectures, reading materials, hands-on exercises, quizzes, and sometimes peer-reviewed assignments. This structured approach ensures you don't miss any critical concepts and build a solid foundation. This resource covers topics essential for success in artificial intelligence and machine learning, including machine learning algorithms, deep learning, NLP, computer vision, and model deployment. The curriculum is structured to build your knowledge progressively — starting with foundational concepts and advancing to real-world applications. By the end, you should be able to: Build apps powered by GPT, Claude, and open-source LLMs Master prompt engineering and context management Implement RAG with vector databases Deploy production-grade GenAI applications Duration: Estimated duration: 6 hours of content, designed to be completed in 1-2 weeks at a comfortable pace. No prior experience is required. This course starts from the absolute basics and gradually builds up complexity. A computer with internet access is all you need to get started. This resource is designed for a wide audience: Students (B.Tech, BCA, MCA, BSc) looking to complement their academic learning with practical, industry-relevant skills Fresh graduates preparing for campus placements or off-campus interviews Working professionals looking to upskill, switch domains, or advance their careers Career changers transitioning from non-tech backgrounds into artificial intelligence and machine learning Freelancers wanting to add new services to their portfolio Self-learners passionate about artificial intelligence and machine learning and wanting structured guidance Pricing: This resource is completely free with no hidden charges. Completing this resource and building related skills can prepare you for roles such as ML Engineer, AI Engineer, Data Scientist, Research Scientist. Realistic salary bands in India (2025-2026), based on Naukri/AmbitionBox data: Freshers / 0-2 years: Rs 8-15 LPA Mid-level / 2-5 years: Rs 18-35 LPA Senior / 5+ years: Rs 40-80 LPA Actual offers vary heavily by city, company tier, and how strong your portfolio or interview performance is. Companies actively hiring in this space include Google, Microsoft, OpenAI, Indian AI startups, research labs. India is the second-largest AI talent pool globally, and the demand far exceeds supply. The Indian AI market is expected to reach $17 billion by 2027. Every major Indian tech company — from Infosys to Reliance to Jio — is investing heavily in AI capabilities. The emergence of generative AI has created entirely new job categories that didn't exist two years ago. ML engineers with LLM experience are commanding Rs 30-60 LPA even at early career stages. Vanderbilt University is a well-established platform trusted by millions of learners worldwide. This particular resource has been selected by our editorial team based on: Content quality — comprehensive coverage with clear explanations Practical focus — emphasis on hands-on skills over pure theory Student outcomes — positive reviews and career success stories Indian relevance — content applicable to the Indian job market and interview patterns Updated curriculum — material reflects current industry practices and tools We regularly review and update our recommendations to ensure they remain relevant and high-quality.
Android App Components - Intents, Activities, and Broadcast Receivers
Vanderbilt University (via Coursera)
This 4 week MOOC builds upon the overview of Java and Android covered in Course 1 by delving deeper into core Android app components, such as intents, activities, and broadcast receivers. You will learn by example how to program these core Android components together with Android concurrency frameworks and basic Java file I/O classes (such as File and InputStream) and Android storage mechanisms (such as Shared Preferences). You'll also learn how to use the Git source code management system. Throughout this MOOC you'll work incrementally on a project involving downloading, storing, and display images from remote websites. Each week you will add additional capabilities to the project, based on material covered in the lecture videos. You'll spend roughly 4 hours per week watching video lectures, taking quizzes, and programming assignments with Java and Android.
Change Management for Generative AI
Vanderbilt University (via Coursera)
Generative AI is revolutionizing industries and transforming the way we work. As organizations embrace these cutting-edge technologies, effective change management becomes crucial to ensure a smooth transition and maximize the benefits of generative AI. In this course, "Change Management for Generative AI," we will delve into the strategies and frameworks necessary to successfully implement and adapt to these transformative technologies. You will learn about the FASTER framework, a comprehensive approach to managing change in the era of generative AI. We will explore each component of the framework, including establishing a strong foundation, aligning stakeholders, implementing safeguards, providing training, embracing evolution, and enabling replication. Through real-world examples and practical insights, you will gain the skills to lead change initiatives and drive the adoption of generative AI in your organization.
Generative AI for University Leaders
Vanderbilt University (via Coursera)
Generative AI is rapidly reshaping industries and the skills that students are going to be expected to have to be employable. As the pace of technological change accelerates, universities must innovate to stay competitive and ensure that they are giving students the skills that they need to be competitive. At the same time, generative AI offers the potential to transform university operations, from automating course scheduling and content creation to streamlining expense reporting and administrative functions. This course provides university leaders with a foundation to understand enough of the key fundamentals of how generative AI works and what it can do to make effective strategic decisions. The course provides a primer on the innovative potential of generative AI across all disciplines and the opportunity for higher education to lead the way in reshaping how students learn and how we work in the future. It shows what is happening in industry and the strategic opportunities for institutions to focus on to help their students excel in the future of work. The course also provides the foundation that an institution needs to get started innovating with generative AI, ranging from policy to platform. The course covers the essential platforms and infrastructure for effective generative AI integration in university settings, offering advice on investment priorities, efficient resource distribution, and pinpointing key advocates to create an interdisciplinary culture of innovation across campus.
ChatGPT + Zapier: Easy Inbox Intelligence for Smarter Email
Vanderbilt University (via Coursera)
Transform your inbox into a powerful source of insights with ChatGPT + Zapier: Easy Inbox Intelligence for Smarter Email! This course shows you how to use generative AI to automatically extract, organize, and synthesize information from your emails, helping you build a comprehensive view of your life—from projects and travel plans to dinner reservations and meetings. With ChatGPT and Zapier, you’ll learn to effortlessly pull together scattered details from multiple emails and create a cohesive picture of what matters. Discover how to automate the extraction of key details from incoming messages and compile them into organized summaries, schedules, or action lists. You’ll explore techniques for using AI to integrate information across different email threads, calendars, and notes, making it easy to track everything you need in one place. By connecting ChatGPT and Zapier, you can set up workflows to monitor updates, track commitments, and ensure nothing slips through the cracks. What You’ll Learn: • Automate Information Extraction: Use ChatGPT to pull details from emails and create summaries that organize projects, travel itineraries, meeting schedules, and more. • Build Comprehensive Overviews: Combine multiple email sources into cohesive reports or schedules, turning scattered messages into a unified picture of your plans. • Stay on Top of Everything: Set up smart workflows to keep track of changing plans, key dates, and ongoing tasks, all from your inbox. Key Course Highlights: • Effortless Inbox Intelligence: Learn to quickly turn email chaos into organized summaries that help you stay on top of your projects, personal plans, and professional commitments. • Real-World Use Cases: See practical examples like organizing international travel itineraries with multiple travelers and keeping track of everything as your plans evolve • Advanced Automation Techniques: Discover how to go beyond simple email filtering by using AI to truly understand and connect t...
The History and Relevance of the Rise of Generative AI
Vanderbilt University (via Coursera)
Dive into the fascinating journey of artificial intelligence, from its theoretical beginnings to today's powerful generative models. This course offers a unique perspective on how AI has transformed over decades, highlighting the crucial developments in deep learning that paved the way for modern AI breakthroughs. After completing this course, you will be able to: Trace the evolution of AI from its early concepts to modern generative models Identify key technological breakthroughs that enabled the rise of generative AI Understand the fundamental differences between traditional AI and generative AI Recognize potential applications and impacts of generative AI across various fields You'll gain insights into the game-changing advancements—like self-supervised learning and transformers—that propelled generative AI to its current prominence. By understanding this history, you'll be better equipped to anticipate future trends and applications in AI. Whether you're an AI enthusiast, a professional looking to leverage AI in your field, or simply curious about the technology shaping our future, this course provides valuable context to help you navigate the exciting world of generative AI.
Claude Code: Software Engineering with Generative AI Agents
Vanderbilt University (via Coursera)
Master AI-Assisted Development with Claude Code: From Fear to 1000X Productivity Transform your software engineering practice by learning to work effectively with AI as your development partner. This comprehensive course takes you from initial skepticism about AI coding tools to confidently leveraging Claude Code for dramatic productivity gains. In just the first few lessons, you'll learn to have Claude Code build entire applications in minutes - complete with user interfaces, databases, and business logic. By the end of this course, you'll know how to orchestrate Claude Code working concurrently across multiple git branches, with parallel AI agents developing different features simultaneously and automatically integrating their work. This isn't about getting better autocomplete - it's about fundamentally changing how software gets built. You'll discover how to treat AI as scalable development labor, implement the "Best of N" pattern to generate multiple solution approaches, and establish robust quality assurance processes that ensure AI-generated code meets professional standards. The course covers essential skills like writing effective CLAUDE.md files for project context, creating reusable commands for common workflows, and managing parallel development streams with git worktrees and AI subagents. Through hands-on exercises and real-world examples, you'll learn to overcome the common fears engineers have about AI tools while building practical systems for code evaluation, documentation generation, and feature development. By the end, you'll have a complete toolkit for scaling your development capabilities and a personalized process that fits your workflow. What You'll Learn: Break free from micromanaging Claude Code and start delegating like a tech lead managing a team of senior developers Write "big prompts" that get Claude Code building entire features instead of generating single functions you copy-paste Use the "Best of N" pattern with Claude C...
Generative AI Database Design & Management with ChatGPT
Vanderbilt University (via Coursera)
Imagine designing databases that evolve with your business, anticipate future needs, and solve problems you haven't even encountered yet. This course teaches you to use AI as your intelligent design partner—creating database architectures neither human nor AI could achieve alone. You'll master AI-powered design techniques that transform traditional database development, leveraging generative AI for schema simulation, automated gap analysis, and AI-facilitated requirement discovery. Together with your AI collaborator, you'll craft schemas that reduce technical debt, minimize migrations, and maintain peak performance through AI-optimized design choices. What You'll Learn: • Test queries against AI-simulated databases before writing any code • Identify design blind spots using AI-powered gap analysis techniques • Have AI interview you with intelligent questions to uncover critical data insights • Convert spreadsheets or photographs into AI-optimized database schemas • Use AI to simulate database performance under various usage scenarios • Create AI-enhanced design packages that document both implementation and reasoning Skills That Will Transform Your Work: • Generate thousands of rows of AI-crafted realistic test data in seconds • Create AI-designed dashboards to validate your design's reporting capabilities • Design AI-optimized migration paths for evolving database needs • Build AI-documented databases that new team members can understand immediately • Explore multiple AI-generated design alternatives to find optimal solutions This course is for anyone who designs or maintains databases—from beginners to seasoned architects. You'll learn practical AI collaboration techniques that dramatically enhance your ability to create systems that are adaptable, resilient, and perfectly aligned with business needs. Join us to master the art of human-AI collaborative database design and create systems that truly stand the test of time.
Faster Together, Enhancing the Recruitment of Marginalized Communities in Clinical Trials
Vanderbilt University (via Coursera)
This course aims to teach people how to enhance the recruitment and retention of individuals from minoritized and marginalized communities in clinical trials. We begin by discussing the importance of diversity in clinical research, the lasting impact of past research abuses, and barriers and facilitators to research participation. Next, we explore community engagement principles, effective communication strategies, ways to increase community knowledge and awareness of clinical research, and outreach to community providers. Last, we discuss recruitment planning, person-centered consent, and retention. The course duration is listed as 8 weeks. However, you can work at your own pace and finish the course faster, if so desired. There is no cost to participate in the course; however, there is a fee for obtaining a completion certificate. Financial aid options are available. CME information: Vanderbilt University Medical Center designates this enduring material for a maximum of 8.0 AMA PRA Category 1 Credit(s)™. For more information, see the first reading assignment in Module 1. Acknowledgments: We would like to acknowledge the following members from the Center for Knowledge Management at Vanderbilt University Medical Center for their expertise and insightful contribution in the development and implementation of the course: Sheila Kusnoor, PhD, Marcia Epelbaum, MA, Lori Harding, MLS, Elizabeth Frakes, MSIS, Helen Naylor, MS, Mallory Blasingame, MA, Taneya Koonce, MSLS, MPH, and Nunzia Bettinsoli Giuse, MD, MLS. We would also like to acknowledge Devan Ray, BA, from the Vanderbilt Institute for Clinical and Translational Research, for her role in project management and contributions to content development. Additionally, we acknowledge ArtMagic Labs, particularly Casey Culver, Victor Tyler, Jake Sucoff, John Martinez, and Robert Eva, for their outstanding work in filming and editing the videos for the course. The Vanderbilt Recruitment Innovation Center leads the eff...
Generative AI for HR Professionals
Vanderbilt University (via Coursera)
Imagine spending your days having meaningful conversations with employees instead of drowning in paperwork. Picture yourself providing truly personalized career guidance instead of rushing through generic development plans. Envision leading strategic initiatives that transform your workplace culture rather than being buried under administrative tasks. This is the promise of AI augmentation - not replacing human judgment, but amplifying your capacity to do the work that only humans can do well. You weren't hired to be a document processor or form filler. You were hired to understand people, solve complex human problems, and create environments where everyone can thrive. But too often, the administrative burden of HR work steals time from these higher-value activities. This course teaches you to use AI as a force multiplier that gives you entirely new capabilities. You'll be able to analyze complex situations from multiple perspectives simultaneously, create personalized solutions at scale, and tackle challenges that would be impossible to handle manually. AI doesn't just handle your routine work - it expands what you can accomplish, letting you provide deeper insights, more comprehensive analysis, and truly customized support while still having time for the face-to-face interactions and strategic thinking that drive real organizational change. What You'll Master: These aren't theoretical concepts - they're practical prompting patterns that will immediately free up hours of your time every week while improving the quality of everything you produce. The Accessible Explanation Pattern: Transform dense technical jargon into crystal-clear insights. Never again struggle to understand complex resumes, job descriptions, or technical documents. Make any expert-level content accessible to your level of understanding. The Transformer Pattern: Take one piece of information and instantly reshape it into multiple formats. Turn performance reviews into timelines, emails, and...
AI Agent Architecture in Java with Generative AI
Vanderbilt University (via Coursera)
Master the Art of Building Intelligent Java Agents That Think, Reason, and Act Unlock the full potential of Java for creating autonomous AI agents that solve complex problems without constant human direction. In this comprehensive course on AI Agents and Agentic AI with Java & Generative AI, you'll learn how to architect sophisticated agent systems that leverage Java's robust ecosystem and enterprise-grade capabilities. This course takes you beyond the foundations covered in the AI Agents and Agentic AI with Java & Generative AI course to explore advanced patterns for building truly intelligent agents in Java. You'll delve into specialized techniques like self-prompting, expert personas, document-as-implementation, and multi-agent orchestration - all implemented with Java's powerful frameworks and libraries. Self-Prompting Patterns in Java: Build agents that dynamically adopt different thinking modes to handle specialized tasks, transforming unstructured data into structured formats with clean Java implementations Java-Based Expert Persona Systems: Implement consultation frameworks where agents can invoke domain experts for specialized knowledge while maintaining clean architecture Document-as-Implementation: Use Java's powerful file handling to create systems where human-readable documents become executable business logic Multi-Agent Collaboration with Java: Design sophisticated memory sharing and coordination mechanisms between specialized Java agents Progress Tracking & Planning: Implement robust planning and reflection capabilities using Java's enterprise-grade tooling Java Agent Safety & Trust Systems: Build transaction management and safety mechanisms that leverage Java's exception handling and security features By the end of this course, you'll be equipped to build complex, enterprise-ready agent systems in Java that can reason across multiple domains, handle complex workflows, and safely interact with real-worl...
The Future of Education with AI: Exploring Perspectives
Vanderbilt University (via Coursera)
The future of education is being shaped by AI, and this course provides a front-row seat to the conversations happening at the ASU+GSV AI Show—one of the leading global events on innovation in learning. In this course, you’ll hear directly from thought leaders, educators, and industry experts who are driving AI’s impact on education. Through exclusive interviews and discussions, we explore key questions: How is AI transforming access to learning? What skills do students need for the future? How can educators adapt to this rapid shift? This course will guide you through insights from some of the most voices in this space. Featured speakers include Kip Glazer, Ardis Kadiu, David Miyashiro, Mushina H. Morris, Merissa Sadler-Holder, Eddie Watson, and Jules White. They bring diverse perspectives from K-12, higher education, and ed-tech innovation, offering a comprehensive look at the evolving role of AI in teaching and learning. This course is your opportunity to engage with these critical conversations and stay ahead in the AI-driven educational landscape.
Agentic AI and AI Agents: A Primer for Leaders
Vanderbilt University (via Coursera)
Forget everything you know about traditional AI. Agentic AI doesn’t just analyze data; it acts on it. From drafting sales emails to updating CRMs, it’s not just a tool—it’s a game-changer. Are you ready to harness its power? Agentic AI combines Generative AI with tools and actions, enabling the creation of "agents" that revolutionize how work is done. Unlike tools that simply generate static outputs, these agents take action—drafting emails directly in your inbox, updating a CRM with client meeting notes, or analyzing sales data and producing a PowerPoint presentation. In the fast-paced world of AI-enhanced work, understanding Agentic AI isn’t optional—it’s your competitive advantage. These intelligent agents are reshaping how tasks are executed, decisions are made, and value is created across industries. By automating repetitive workflows and enhancing high-value tasks, they empower teams to focus on innovation and strategy. Agentic AI is transforming industries, and this course will ensure you’re leading the charge, not playing catch-up. Understanding their capabilities and limitations is essential for staying competitive in this rapidly evolving landscape. This course demystifies Agentic AI, teaching you how these agents work and how to design them to suit your needs. By the end, you’ll not only know how to differentiate genuine AI innovation from overhyped gimmicks but also be equipped to build tools that deliver tangible value. Whether you’re in business, technology, or leadership, this course will help you stay ahead of the curve.
ChatGPT Advanced Data Analysis
Vanderbilt University (via Coursera)
ChatGPT Advanced Data Analysis is going to transform tasks by helping amplify your productivity and supporting your creativity. ChatGPT Advanced Data Analysis can help you augment your intelligence and automate tasks, such as: 1. Turning an Excel file into visualizations and then slides inside a PowerPoint presentation; extracting data from a series of PDFs 2. Answering questions about what is in the PDFs, and visualizing the data; automatically determining if a receipt complies with a travel policy captured in a PDF 3. Transforming a document into a training presentation and associated quizzes; reading and reorganizing a set of documents based on what they contain 4. Producing social media and marketing content from a series of documents or video transcripts 5. Automating resizing and editing of videos/images while also cataloging them in a CSV Anyone with ChatGPT Advanced Data Analysis can tap into these capabilities without any prior experience in programming. The course teaches you how to converse with ChatGPT Advanced Data Analysis to accomplish these tasks, how to think about problem solving, and what types of tasks are good fits for the tool. You will learn a wide range of building blocks that you can apply in your own work and life. Large language models respond to instructions and questions posed by users in natural language statements, known as “prompts”. Although large language models will disrupt many fields, most users lack the skills to write effective prompts. Expert users, who understand how to write good prompts, are orders of magnitude more productive and can unlock significantly more creative uses for these tools. This course will introduce you to prompt writing skills that target ChatGPT Advanced Data Analysis.
ChatGPT Meal Planning: Effortlessly Plan and Cook with AI
Vanderbilt University (via Coursera)
Tired of the daily meal planning grind? Discover how to harness the power of ChatGPT to revolutionize your meal planning and cooking routine! In ChatGPT Meal Planning: Effortlessly Plan and Cook with AI, you'll learn how to transform the way you approach meals, using AI to create customized plans that fit your schedule, dietary needs, and preferences—without the stress. By the end, you will know exactly how to use Generative AI to act like your personal chef and inspire you with creative new recipes. This course will teach you to generate personalized meal plans tailored to your lifestyle, taking into account everything from busy workdays to special family gatherings. Whether you’re dealing with time constraints, picky eaters, or limited ingredients, ChatGPT will become your go-to tool for simplifying the process. You'll learn how to create detailed recipes from high-level meal ideas, explore recipe variations for variety and creativity, and even craft family-friendly menus that everyone will love. Here are some of the things you will learn: Turn Fridge Leftovers into Instant Meals: Learn how to snap a picture of what's left in your fridge and have ChatGPT create quick, delicious recipes based on what you already have—no more wasted food or last-minute grocery runs. Seamlessly Integrate Your Calendar: Discover techniques to sync your digital or physical calendar with ChatGPT for hands-free meal planning, ensuring your meals fit perfectly into even the busiest of schedules. Create a "Meal Planning Persona" for You or Your Family: Build an intelligent meal planning profile that knows your favorite dishes, where you shop, your dietary preferences, and how much time you have to cook. Let ChatGPT become your personal meal planner that knows exactly what you need before you even ask. Blow Your Guests Away with Creative Fusion Cuisine: Master methods to create extraordinary fusion dishes that mix the best flavors of world cuisines. Whether it's a Mexican-Kore...
Generative AI for Kids, Parents, and Teachers
Vanderbilt University (via Coursera)
My son is going to grow up in a completely different world that is filled with generative AI (e.g., ChatGPT, Claude, LLama, etc.). I think this is a world of possibility, creativity, and deep thought that will enrich the way we think and solve problems. I want to make sure that my son is set up for success in this new world and understands how to use generative AI in a way that helps him learn, create, and solve problems. Even though generative AI seems obvious to use, it isn't. Really learning to innovate and succeed with generative AI requires a change in mindset about the way we use it and how we solve problems. We have to teach people to think more, not less about what they are doing. I spent the last year working with my son to empower him with the skills to use generative AI to augment and amplify his critical thinking and creativity. I distilled this teaching into a series of courses that you can use to help teach your kids, either at home or in the classroom, these same skills. This is the first of these courses. Some of the things that we have done that you will learn to do with your kids: Take pictures of anything and have generative AI turn the photos into world records that you can fact check Interactively brainstorm how to build anything out of any material using generative AI as your partner Invent new games from photos of everyday objects I teach a course on Prompt Engineering, which is the study of how you converse and solve problems with generative AI that 100,000s of people have enrolled in. I have gotten to hear about how companies all over the world are changing the future of work with generative AI. These courses are specifically designed to help you teach kids to succeed in this new world. This course is meant for parents and teachers to do with kids. You watch the videos, preview the exercises, and then lead kids through the fun activities. You decide what to show and how to best communicate with your kids. Along the way, not only...
Generative AI Primer
Vanderbilt University (via Coursera)
ChatGPT and other large language models are going to be more important in your life and business than your smartphone, if you use them right. ChatGPT can tutor your child in math, generate a meal plan and recipes, write software applications for your business, help you improve your personal cybersecurity, and that is just in the first hour that you use it. The course will give you a primer that covers what Generative AI is, basic prompt engineering, and how you can innovate with Generative AI. You will learn the ACHIEVE framework for using Generative AI to innovate in a way that augments and amplifies human creativity and problem solving rather than supplanting people. You will learn how Generative AI is going to replace the GUI and programming as our dominant interface to computing and why you will be using it every day at work.
AI Agents with Model Context Protocol & Typescript
Vanderbilt University (via Coursera)
Build AI Agents That Actually Work AI agents are everywhere—but most of them fail in frustrating, unpredictable ways. They get confused, waste tokens, hit dead ends, and require constant babysitting. This course teaches you the patterns and architectures that separate agents that struggle from agents that succeed. Using TypeScript and the Model Context Protocol (MCP), you'll learn to build AI agents from the ground up—and more importantly, you'll learn why certain designs work while others fall apart. What You'll Learn: Build MCP Tool Servers — Create the bridge that lets AI agents interact with any system: filesystems, databases, APIs, or your own custom tools Master the Agent Loop — Understand the universal pattern every AI agent follows: PERCEIVE → DECIDE → ACT → OBSERVE → REPEAT Connect agents to tools — Wire up LLMs to discover, select, and execute tools autonomously The Patterns That Make Agents Reliable: Response-as-Instruction — Your tools don't just return data—they guide agent behavior in real-time. Learn to design tool responses that teach the agent what to do next, when to stop, and how to communicate results. Failing Forward — Turn errors from dead ends into stepping stones. Design error messages that teach agents how to recover—automatically, without human intervention. For the first time in computing history, your error messages have a reader that can actually do something about them. Intelligence Budget — Every token in the context window is precious attention. Learn to maximize signal and minimize noise—pre-digesting data in tools, using scripted orchestration for mechanical work, and reserving the agent's cognitive resources for decisions that actually require intelligence.
From Data to Decisions: Finding Patterns with AI
Vanderbilt University (via Coursera)
This course teaches students how to generate univariate graphics, such as histograms and box plots, using generative AI tools to automate and streamline the analysis process. Students will explore conditional means through statistical methods like ANOVA and t-tests, while also using AI to create and interpret visualizations, such as bar charts and dot plots. A key focus will be on leveraging AI to both carry out analyses and generate clear, data-driven explanations of the results. By the end, students will confidently utilize AI to enhance their data analysis and communication skills.
Model Context Protocol for Leaders: Generative AI Agents
Vanderbilt University (via Coursera)
Your AI can write the perfect email, but can it actually send it? It can analyze your calendar, but can it schedule the meeting? The gap between AI's intelligence and its ability to take action has been the biggest barrier to true automation—until Model Context Protocol (MCP) broke it wide open. MCP is the revolutionary protocol that gives AI agents actual agency—the power to discover, select, and use your business tools autonomously. When you tell an AI agent to "add this travel expense," MCP enables it to list your spreadsheet rows, identify what's missing, and add the expense directly—no human intervention required. It's the difference between an AI that tells you what to do and one that does it for you. Think of MCP as the universal translator between AI intelligence and your computer systems. It allows AI agents to automatically discover available tools—from email senders to CRM updaters to database queries—and use them in intelligent sequences to solve complex problems. The AI enters a powerful loop: assess the task, select a tool, execute through MCP, evaluate results, and repeat until the job is done. You provide the goal; the AI handles the execution. This course teaches anyone—regardless of technical background—how Model Context Protocol actually works. We skip the technical minutiae and focus on the concepts that matter: how MCP enables AI autonomy, how it uses tools, and why it's transformative. You'll learn to integrate MCP into the AI tools you already use, like ChatGPT and Claude, transforming them from smart assistants into autonomous agents that can check your calendar, update your spreadsheets, send your emails, and manage your workflows. This isn't about becoming a programmer; it's about understanding the technology well enough to design solutions, lead implementations, and strategize competitive advantages. By the end of this course, you'll possess the knowledge to evaluate MCP solutions, identify automation opportunities, and lead your organi...
Building Cloud Services with the Java Spring Framework
Vanderbilt University (via Coursera)
This MOOC describes by example how to build cloud services via the use of object-oriented design techniques; Java programming language features; Java Servlets, the Java Spring Framework; and cloud computing platforms, such as Amazon Web Services. Due to the importance of building secure and scalable mobile/cloud platforms, this MOOC will not only show you how to build cloud services, but how to do so securely, scalably, and efficiently. Security and scalability topics will be woven into discussions of cloud service creation so that students learn, from the start, how to create robust cloud services.
Android App Components - Services, Local IPC, and Content Providers
Vanderbilt University (via Coursera)
This 4 week MOOC builds upon the core Android app components and concurrency frameworks covered in Course 2 by focusing on started and bound services, local inter-process communication (IPC), and content providers. Case study apps will be examined from multiple perspectives to learn how to program these app components using Android's material design paradigm. Students will work incrementally on a hands-on project involving a material design-based RSS reader app. Each week you will add additional capabilities to the project, based on material covered in the lecture videos. You'll spend roughly 4 hours per week watching video lectures, taking quizzes, and programming assignments with Java and Android.
Prompt Engineering for ChatGPT
Vanderbilt University (via Coursera)
ChatGPT and other large language models are going to be more important in your life and business than your smartphone, if you use them right. ChatGPT can tutor your child in math, generate a meal plan and recipes, write software applications for your business, help you improve your personal cybersecurity, and that is just in the first hour that you use it. This course will teach you how to be an expert user of these generative AI tools. The course will show amazing examples of how you can tap into these generative AI tools' emergent intelligence and reasoning, how you can use them to be more productive day to day, and give you insight into how they work. Large language models respond to instructions and questions posed by users in natural language statements, known as “prompts”. Although large language models will disrupt many fields, most users lack the skills to write effective prompts. Expert users, who understand how to write good prompts, are orders of magnitude more productive and can unlock significantly more creative uses for these tools. This course introduces students to the patterns and approaches for writing effective prompts for large language models. Anyone can take the course and the only required knowledge is basic computer usage skills, such as using a browser and accessing ChatGPT. Students will start with basic prompts and build towards writing sophisticated prompts to solve problems in any domain. By the end of the course, students will have strong prompt engineering skills and be capable of using large language models for a wide range of tasks in their job, business, personal life, and education, such as writing, summarization, game play, planning, simulation, and programming.
Data Management for Clinical Research
Vanderbilt University (via Coursera)
This course presents critical concepts and practical methods to support planning, collection, storage, and dissemination of data in clinical research. Understanding and implementing solid data management principles is critical for any scientific domain. Regardless of your current (or anticipated) role in the research enterprise, a strong working knowledge and skill set in data management principles and practice will increase your productivity and improve your science. Our goal is to use these modules to help you learn and practice this skill set. This course assumes very little current knowledge of technology other than how to operate a web browser. We will focus on practical lessons, short quizzes, and hands-on exercises as we explore together best practices for data management.
ChatGPT & Zapier: Agentic AI for Everyone
Vanderbilt University (via Coursera)
Agentic AI is a type of AI that combines Generative AI with tools and actions, allowing us to build "agents" to assist us with everyday tools like Gmail, Office365, Google Sheets, Salesforce, etc. These agents can perform tasks on our behalf, such as updating a spreadsheet or sending an email. There are classes that teach these Agentic AI concepts, but they are geared towards programmers. If you aren't a programmer, they won't teach you how to build agents to help with your daily tasks. This class will teach you how to use ChatGPT and Zapier to build your own agents to help prioritize tasks, keep track of expenses, plan meals and shopping lists, etc. These won't be tools that require you to cut and paste the results back into an email; these will be tools that can directly create a draft email and put it into your email account or allow you to snap a picture of a receipt on the go and have it show up in a spreadsheet. These agents can automate and take action for you. By the end of this class, not only will you understand state-of-the-art aspects of Agentic AI, but you will have built your own Travel Expense Agent. Your agent will be able to take a picture of a receipt or a description of an expense and catalog it into a Google Sheet. It will check your expense with another agent for completeness, ensure the expense isn't already in the spreadsheet, and even draft an email to your administrator with a simple reimbursement report. This course will transform the way you work.
Trustworthy Generative AI
Vanderbilt University (via Coursera)
We see lots of news reports of Generative AI tools, such as ChatGPT, making mistakes and producing inaccurate information. Many of these mistakes happen because humans use the tools in the wrong way - trying to solve unsuitable problems and not thinking about risk. Hallucination isn't a bug, it's a feature when you approach problems correctly. This course teaches techniques for determining if a problem fits Generative AI's capabilities, framing problems to reduce risk, prompt engineering for trust, and appropriate human engagement in the process. Students learn concrete prompt designs, how to check outputs, how to use Generative AI for ideation and creation, ways to augment human skills, and more ethical, beneficial applications. The course will show how you can: Leverage prompt engineering techniques to generate more reliable outputs Master methods to verify and validate outputs Frame problems in alternative ways to reduce risk Apply generative AI for creative ideation Use Generative AI in ways that augment rather than replace human reasoning and creativity
Generative AI for Legal Services Primer
Vanderbilt University (via Coursera)
This course covers what Generative AI is and its applications to a variety of tasks in the legal field. The course will cover ethics and privacy, basic prompt engineering strategies for legal use cases, and how to leverage Generative AI to augment your legal expertise. This is a rapidly advancing area and a primary goal of this course is to prepare everyone for the pace of change that is taking place and to develop a mindset of continuous curiosity that will enable lawyers to adapt along with the technology
Capstone MOOC for "Android App Development"
Vanderbilt University (via Coursera)
The Capstone project integrates material from throughout the Android App Development Specialization to exercise and assess the ability of learners to create an interesting Android app. Learners will apply knowledge and skills learned in previous MOOCs in this Specialization, including Java programming features; Android activity, broadcast receiver, service, and content provider (plus SQLite) components; and unit, integration, and user interface testing. The project itself is similar in scope to previous assignments in the earlier MOOCs in the Specialization. However, it is intentionally designed to enable learners to create a customized app that demonstrates their creativity and mastery of the Specialization topics.
Java for Android
Vanderbilt University (via Coursera)
This MOOC teaches you how to program core features and classes from the Java programming language that are used in Android, which is the dominant platform for developing and deploying mobile device apps. In particular, this MOOC covers key Java programming language features that control the flow of execution through an app (such as Java’s various looping constructs and conditional statements), enable access to structured data (such as Java's built-in arrays and common classes in the Java Collections Framework, such as ArrayList and HashMap), group related operations and data into classes and interfaces (such as Java's primitive and user-defined types, fields, methods, generic parameters, and exceptions), customize the behavior of existing classes via inheritance and polymorphism (such as subclassing and overriding virtual methods). Learners will apply these Java features in the context of core Android components (such as Activities and basic UI elements) by applying common tools (such as Android Studio) needed to develop Java programs and useful Android apps. Learners will work on several hands-on projects throughout the MOOC, i.e., each week will require learners to write solutions to programming assignments that reinforce the material covered in the lecture videos. There will be roughly 4-6 hours of student engagement time per week, including video lectures, quizzes, and programming assignments.
ChatGPT for Project Management: Execution, Tracking, Success
Vanderbilt University (via Coursera)
In "ChatGPT for Project Management: Execution, Tracking, Success," you’ll learn how to harness the power of generative AI to streamline project management during the critical execution phase. This course focuses on using ChatGPT to synthesize information from various sources, such as emails and reports, into cohesive documents that accurately track project progress. You'll discover how AI can enhance scheduling, make meetings more engaging, and transform meeting transcripts into actionable work products. You’ll also explore how multimodal prompting can facilitate real-time team collaboration, enabling AI-driven brainstorming and the production of deliverables directly from your team’s interactions. The course covers advanced techniques, such as using AI to conduct "pre-work" on tasks, draft key project outputs, and assist with producing detailed documentation. By the end of this course, you’ll be equipped with practical, AI-powered strategies to optimize your project execution and help you succeed.
Generative AI for Leaders
Vanderbilt University (via Coursera)
Leaders are constantly seeking innovative tools to amplify their impact. Dive into the realm of Generative AI, a groundbreaking technology poised to redefine the leadership landscape more profoundly than the Internet itself. This course offers a comprehensive journey into understanding, applying, and mastering Generative AI as a robust tool to amplify leadership capabilities. You will gain hands-on experience that teaches you to use Generative AI for: Agenda Architecting: Let Generative AI craft impeccable agendas for you. Say goodbye to oversight and hello to perfectly planned meetings. Proposal Proficiency: Dive deep into complex proposals with AI by your side. Identify risks, ambiguities, and potential pitfalls with laser-sharp precision. Your Private Think-Tank: Use Generative AI as a confidential thought partner. Brainstorm, strategize, and refine your ideas with an AI confidant that's always ready. Masterful Communication: Draft emails, documents, and crucial materials with eloquence and precision. Let Generative AI be your co-author, ensuring your communications resonate with impact. Navigating HR Dynamics: Explore challenging HR conversations with added insight. Generative AI assists you in understanding nuances and guiding delicate conversations towards positive outcomes. Seamless Leadership Transitions: Whether it's you moving up the ladder or a team member stepping into a new role, Generative AI aids in ensuring smooth transitions. Plan, strategize, and execute leadership handovers with unparalleled confidence. In addition to these key hands-on tasks, you will quickly come up to speed on how to innovate with Generative AI, and explore: Deep Dive into Generative AI: Grasp the underlying principles of Generative AI and its transformative potential. Equip yourself to make critical decisions about implementing Generative AI in your organization, ensuring you stay ahead in the modern leadership curve. Augmented Intelligence - The Ne...
Chat with Your Data: Generative AI-Powered SQL Data Analysis
Vanderbilt University (via Coursera)
Imagine turning your database into a conversation partner that not only answers your questions but visualizes insights, finds patterns you've missed, and helps fix your queries. This isn't science fiction—it's the power of Generative AI applied to SQL and data analysis. Traditional database interaction requires technical expertise, writing complex queries, and switching between multiple tools to analyze and visualize results. But what if you could simply have a conversation with your data? What if you could ask questions in plain language and receive immediate, actionable insights? This course teaches you how to revolutionize your relationship with databases through ChatGPT-assisted analysis. You'll learn powerful techniques to establish accurate database context, collaboratively explore meaningful questions, generate precise SQL queries, and transform raw results into compelling visualizations—all through natural conversation with AI. All of these techniques are simple for anyone to use with just ChatGPT and your database. We'll explore proven patterns like the CLUE framework for establishing database context, the experimental query generation approach for building complex queries, and the TRUST method for verifying your results. You'll discover how to design visualization-first queries, build reproducible analysis pipelines with the CAPTURE pattern, and efficiently troubleshoot SQL issues using the DEBUG framework. Whether you're a data analyst seeking to accelerate your workflow, a business professional who needs insights without coding expertise, or a database administrator looking to expand your toolkit, this course equips you with immediately applicable skills. You'll learn to extract more value from your existing data while dramatically reducing the time and technical barriers traditionally associated with database analysis. By the end of this course, you'll transform how you interact with databases—moving from rigid, technical queries to fluid, insight...
AI Agents in Java with Generative AI
Vanderbilt University (via Coursera)
AI Agents Are the Next Leap in Software. Learn to Build Them in Java. AI agents aren’t passive tools. They think, act, and solve problems—without waiting for instructions. That’s the future of software. And in this course, you’ll learn how to build it. Frameworks come and go. Principles last. This course cuts through the noise to teach you how AI agents really work—using rock-solid Java. Forget tutorials on trendy APIs that’ll be dead by next quarter. You’ll learn to build AI agents from the ground up. No fluff. No shortcuts. Just the core architecture that powers intelligent systems—knowledge that stays useful no matter how fast the landscape shifts. In this course, you will: Master Java-based agent architectural fundamentals - Understand the core GAME components (Goals, Actions, Memory, Environment) that make AI agents tick and how they work together in a cohesive Java system Leverage Java's strengths for efficient agent development - Use Java's reflection, annotation processing, and strong typing to create robust, maintainable agent frameworks with minimal boilerplate code Rapidly prototype and implement Java agents - Learn techniques to quickly design Java agent capabilities with prompt engineering before writing a single line of code, then efficiently translate your designs into working Java implementations Connect Java AI agents to real-world systems - Build Java agents that can interact with file systems, APIs, and other external services Create Java-powered tool-using AI assistants - Develop Java agents that can analyze files, manage data, and automate complex workflows by combining LLM reasoning with Java's extensive libraries and functionality Build Java developer productivity agents - Create specialized Java agents that help you write code, generate tests, and produce documentation to accelerate your software development process Why Principles Matter More Than Frameworks The AI landscape is changing weekly, but the core principles ...
ChatGPT + Cybersecurity: AI-Powered Tabletops & Training
Vanderbilt University (via Coursera)
Struggling to prepare your team for unexpected cybersecurity threats? Imagine having an AI partner that can help you build hyper-realistic tabletop scenarios, practice decision-making under pressure, and uncover blind spots—all while saving time and resources. This course will guide you on a journey to revolutionize your approach to cybersecurity training by integrating ChatGPT into your tabletop exercises, ensuring your organization is ready for the real game. What You'll Learn: Create Dynamic and Realistic Cybersecurity Scenarios: Use ChatGPT to design interactive scenarios with branching decision trees. Craft exercises that adapt to participants’ choices, pushing them to think critically about complex challenges while uncovering new angles of attack. Perform Individualized, Targeted Practice with Micro-Tabletops: Learn how to use ChatGPT to create "micro-tabletops," small-scale exercises that allow individual team members or small groups to focus on their specific responsibilities and tools. These targeted simulations enable frequent practice, iterative hardening of specific domains (e.g., Active Directory or Okta), and integration with broader team exercises to ensure overall organizational preparedness. Master the Flipped Interaction Pattern for Training: Discover how to let AI take the lead in tabletop facilitation. This unique approach allows ChatGPT to simulate evolving incidents, ask probing questions, and dynamically adapt based on your team’s responses—making every session a tailored learning experience. Inject Real-World Pressure into Your Scenarios: Learn how to add authentic tension to decision-making exercises. With ChatGPT, you can create scenarios that mimic the real-world ripple effects of cybersecurity breaches, such as regulatory deadlines, stakeholder complaints, or operational disruptions. Optimize Your Team’s Response Through Iterative Practice: Transform the way your organization practices cybersecurity. Generate instant feedback, ident...
ChatGPT + Zapier: Automate Email Replies with AI
Vanderbilt University (via Coursera)
Tired of spending hours manually replying to emails? In ChatGPT + Zapier: Automate Email Replies with AI, you’ll learn how to transform your inbox management process by setting up automated AI-driven email replies. This course will show you how to connect labeled emails and folders to workflows that draft responses while you triage your inbox. By the time you’ve finished organizing, ChatGPT will have prepared reply drafts for you to review and send. You’ll master setting up ChatGPT with customized instructions using a Google Document or another note-taking tool, allowing you to teach ChatGPT how to adjust its responses based on different situations. Enhance your email responses with smart customization by feeding ChatGPT useful instructions like frequently asked questions, typical responses, escalation guidelines, and personal preferences for tone or formality. Provide dynamic information, such as upcoming travel plans, meeting availability, or recent project updates, to ensure replies are accurate, context-aware, and in line with your communication style. Incorporate templates for common scenarios (e.g., scheduling meetings, responding to customer inquiries, or sharing project status updates) to make your automated responses even more efficient and relevant. You will learn skills to help tackle common email pain points, such as: • Avoiding back-and-forth scheduling: Automatically include preferred meeting times or suggest open slots based on your calendar. • Quickly addressing repeated queries: Generate detailed responses to FAQs or recurring requests without starting from scratch each time. • Efficient escalation handling: Provide clear next steps or contact details for further assistance, using escalation guidelines for common issues. Whether you’re looking to streamline client communication, speed up internal responses, or simply reduce the time spent on email, this course will equip you with the tools you need to automate your inbox efficiently and effec...
Microsoft 365 Copilot: Personal Productivity for All
Vanderbilt University (via Coursera)
Dive into the next wave of digital productivity with our course centered on Microsoft 365 Copilot. As impactful as the smartphone revolution, Microsoft 365 Copilot is poised to redefine how we approach myriad tasks, bringing the nuanced capabilities of generative AI to your fingertips. With this course, discover how to leverage this powerful assistant in your daily routine, transforming every challenge into an opportunity for excellence. Explore innovative ways Microsoft 365 Copilot can accelerate your workflow while ensuring precision and depth. For instance, after a brainstorming session on a Teams call, Copilot can help you sift through the conversation, pinpointing ambiguities and providing clarity that leads to a fortified plan of action. It can also adapt written content to resonate with specific audiences, turning generic messages into targeted communications crafted to engage and convert. This course transcends beyond merely getting things done—it's about achieving the highest standards in problem-solving and producing solutions that endure. Microsoft 365 Copilot doesn't offer just speed; it offers sophistication. Learn to invoke its advanced AI to review drafts, anticipate project hurdles, or reframe proposals, ensuring your deliverables are not just completed, but are crafted with the insight and finesse of a seasoned expert. By embedding Microsoft 365 Copilot's intelligence into your processes, you'll raise the bar on what it means to work smart—creating, collaborating, and conquering tasks with unprecedented confidence and creativity.
Programming for a Networked World
Vanderbilt University (via Coursera)
Want to learn the basics of computer programming in a fun and innovative way? This course introduces computer programming using an educational block-based visual programming environment called NetsBlox (https://editor.netsblox.org/), emphasizing modern computer science concepts like networking, the internet, and distributed computing. The curriculum is hands-on, focusing on translating ideas into working computer programs and developing a mastery of practical computational literacy. After completing this course, you will have a solid foundation to learn professional languages like Python, Java, etc. The course is especially suitable for K12 teachers and students who want to get a gentle introduction to computer science.
AI Agents with Model Context Protocol
Vanderbilt University (via Coursera)
Build AI Agents That Actually Work AI agents are everywhere—but most of them fail in frustrating, unpredictable ways. They get confused, waste tokens, hit dead ends, and require constant babysitting. This course teaches you the patterns and architectures that separate agents that struggle from agents that succeed. Using Python and the Model Context Protocol (MCP), you'll learn to build AI agents from the ground up—and more importantly, you'll learn why certain designs work while others fall apart. What You'll Learn: Build MCP Tool Servers — Create the bridge that lets AI agents interact with any system: filesystems, databases, APIs, or your own custom tools Build a Research Agent - Create your own research agent that can explore your computer and help answer questions with documents, find that missing data, or explain how code works. Master the Agent Loop — Understand the universal pattern every AI agent follows: PERCEIVE → DECIDE → ACT → OBSERVE → REPEAT Connect agents to tools — Wire up LLMs to discover, select, and execute tools autonomously The Patterns That Make Agents Reliable: Response-as-Instruction — Your tools don't just return data—they guide agent behavior in real-time. Learn to design tool responses that teach the agent what to do next, when to stop, and how to communicate results. Failing Forward — Turn errors from dead ends into stepping stones. Design error messages that teach agents how to recover—automatically, without human intervention. For the first time in computing history, your error messages have a reader that can actually do something about them. Intelligence Budget — Every token in the context window is precious attention. Learn to maximize signal and minimize noise—pre-digesting data in tools, using scripted orchestration for mechanical work, and reserving the agent's cognitive resources for decisions that actually require intelligence.
Mastering Programming with MATLAB
Vanderbilt University (via Coursera)
The course builds on the foundation laid by the first course of the Specialization called “Introduction to Programming with MATLAB.” It covers more advanced programming concepts such as recursion, vectorization, function handles, algorithm efficiency and others. At the same time, it presents many features that make MATLAB a powerful programming environment for engineering and scientific computing, such as its support for object oriented programming, the new user interface design environment and Live Scripts. By the end of this course, you will be familiar with more advanced computer programming concepts, able to write more efficient code, and able to create object oriented MATLAB applications with graphical user interfaces.
Functional Programming with Java and Threads
Vanderbilt University (via Coursera)
This course provides an in-depth journey through modern Java object-oriented and function programming concepts and features, and explores how to apply these concepts and features to implement efficient and scalable concurrent programs using very modern Java features like virtual threads. The first week gives an overview of Java object-oriented and functional programming paradigms. The second and third week delve into Java functional programming features, such as lambda expressions, method references, and functional interfaces. The final week explores the intricacies of very modern Java platform threads, virtual threads, as well as Java's asynchronous computation features, such as Future & FutureTask. After completing this course, you'll gain a deep understanding of both object-oriented and functional programming concepts and features in Java, along with the ability to apply these concepts and features to develop multi-threaded programs. To illustrate key points, we walk through numerous case studies, all of which are available in open-source form from my GitHub repository.
MATLAB을 사용한 프로그래밍 소개
Vanderbilt University (via Coursera)
이 과정에서는 이전 경험이 거의 또는 전혀 없는 사람들에게 컴퓨터 프로그래밍을 가르칩니다. 이 프로그램은 MATLAB이라는 프로그래밍 시스템과 언어를 사용하는데, 이유는 배우기 쉽고 기능이 많고 엔지니어와 기타 전문가에게 매우 유용하기 때문입니다. MATLAB은 숫자 조작과 관련된 문제를 해결하는 중간 규모의 프로그램을 작성하기에 훌륭한 특수 목적 언어입니다. 언어 설계상 몇 줄로 강력한 프로그램을 작성할 수 있습니다. 문제는 상대적으로 복잡할 수 있지만, 문제를 해결하는 MATLAB 프로그램은 상대적으로 간단합니다. 상대적이라 함은, C++ 또는 Java와 같은 범용 언어로 작성된 동등한 프로그램이라는 것입니다. 그 결과, MATLAB은 자연 과학부터 공학의 모든 분야, 금융 등 다양한 영역에서 사용되고 있으며 산업계에서도 많이 사용되고 있습니다. 따라서 MATLAB에 대한 탄탄한 배경 지식은 오늘날의 취업 시장에서 없어서는 안 될 필수 기술입니다. 그렇지만 이 과정은 MATLAB 튜토리얼이 아닙니다. MATLAB을 사용하여 컴퓨터 과학 및 프로그래밍의 일반적인 개념을 설명하는 프로그래밍 입문 과정입니다. 이 과정을 성공적으로 마친 학생은 컴퓨터 과학의 일반 개념에 익숙해지고 프로그래밍의 일반 개념을 이해하며 MATLAB 사용에 대한 탄탄한 기초를 얻게 됩니다. 이 과정을 수강하는 학생은 과정 기간 동안 MATLAB Online 라이선스를 무료로 받게 됩니다. 학생들은 이 과정의 기반이 되는 전자책을 참조하는 것이 좋습니다. 이러한 리소스에 대한 자세한 정보는 오른쪽의 리소스 메뉴에서 찾을 수 있습니다.
Advanced Prompt Engineering for Everyone
Vanderbilt University (via Coursera)
Unlock the full potential of generative AI and become a master of prompt engineering. Dive deeper into how you can use In-context Learning to build better and more reliable prompts. See how Retrieval Augmented Generation (RAG) works and what can go wrong that you can counteract with fact-checkable prompt formats. Overcome your struggles in getting the right output from generative AI models with template-based output formats to achieve precision in your interactions with AI models. Tap into powerful AI capabilities for tasks ranging from social media comment analysis to survey results interpretation and beyond. This course will empower you with the skills needed to build exceptional prompts, using simple techniques, such as preference-driven refinement, and become and expert in leveraging generative AI for productivity and creativity. What You Will Learn: In-Context Learning: Understand how to provide context within prompts to guide AI models towards more accurate and relevant outputs. Learn techniques to embed contextual information that enhances the model’s understanding and performance. Retrieval Augmented Generation (RAG): Explore how to integrate retrieval systems with generative models to provide more precise and informed responses. This module covers the mechanisms to combine the strengths of both retrieval and generation. Template Pattern and Examples: Master the art of crafting template-based prompts to achieve consistent and desired outputs. Learn how to tell generative AI to fit its output into your format and overcome struggles with getting exactly what you want. Tapping Into AI Capabilities for Everyday Use: Delve into practical applications such as analyzing social media comments, interpreting survey results, and other everyday tasks where generative AI can make a significant impact. Gain hands-on experience with real-world examples. Building Great Prompts: Discover simple methods for constructing effective prompts. Learn how preference-driven ref...
Generative AI Deep Research: Strategic AI Edge for Leaders
Vanderbilt University (via Coursera)
Transform Your Decision-Making with AI Deep Research. While your competitors spend weeks gathering information through traditional research methods, you'll master cutting-edge agentic AI tools that conduct comprehensive, autonomous investigations in minutes. This advanced course teaches executives and strategic leaders how to leverage generative AI's most powerful research capabilities to create sustainable competitive advantages. What is Deep Research? Deep research is an advanced AI capability that works like hiring a team of PhD researchers who autonomously investigate complex topics for 10-15 minutes, gathering information from multiple sources, cross-referencing findings, and producing comprehensive 10-20 page reports with proper linked citations. Unlike standard AI chat where you get instant but limited responses with potentially incorrect citations, deep research agents conduct extended self-dialogue, adapt their search strategies based on what they discover, and synthesize vast amounts of current information into cohesive analysis—delivering the depth and rigor of professional consulting work in a fraction of the time and cost. Best of all, they provide fact checkable citations and links. What You'll Master: Instant Strategic Consulting: Deploy AI agents that deliver PhD-level analysis in 15 minutes instead of hiring consultants for weeks. Get comprehensive market assessments, competitive intelligence, and strategic recommendations when traditional consulting isn't feasible, affordable, or fast enough. Elite Talent Discovery: Systematically identify and evaluate top performers across any domain with AI Deep Research—from "Java AI developers in Nashville" to "automotive specialists for vintage Toyotas." Move beyond superficial LinkedIn searches to evidence-based expertise verification that reveals genuine competence. Advanced Procurement Intelligence: Generate detailed buying or procurement guides tailored to your specific situation and constraints with...
Integrating Generative AI into Project Management
Vanderbilt University (via Coursera)
After taking this course, learners will be able to effectively integrate generative AI tools (Large Language Models, LLMs, like ChatGPT) into their project management workflows to enhance efficiency, communication, and decision-making while maintaining ethical standards and data security. • Learners will be able to apply practical AI-driven solutions to automate repetitive tasks and enhance daily project management operations. • Learners will be able to use generative AI to improve the accuracy of team communication • Learners will be able to identify and address potential ethical concerns and limitations when implementing AI in project management. This course teaches how to effectively integrate generative AI into project management to automate tasks, enhance communication, and maintain ethical standards. Learners will understand the balance between AI capabilities and human expertise, ensuring responsible and efficient project outcomes.
Qualitative Methods for Quantitative People (with GenAI)
Vanderbilt University (via Coursera)
Qualitative Methods for Quantitative People (with GenAI) is a course designed for individuals with a strong quantitative background who want to explore the power of qualitative analysis through the lens of Generative AI (GenAI). This course introduces foundational concepts of qualitative analysis, guiding learners through the process of interpreting concepts, experiences, and nuanced data. It emphasizes how qualitative insights complement quantitative methods, enabling more comprehensive decision-making. Throughout the course, learners will gain hands-on experience in using Large Language Models (LLMs) for tasks such as data-driven decision-making, resource allocation, and qualitative interpretation of complex information. They will explore real-world scenarios, leveraging AI to extract insights from surveys, documents, and discussions, ultimately fostering better collaboration and a deeper understanding of diverse data sets. Key topics include qualitative versus quantitative analysis, leveraging AI for creating living documents, navigating biases, and maintaining human oversight in AI-driven processes. This course is ideal for those looking to enhance their analytical toolkit with qualitative methods supported by cutting-edge AI technologies. By the end of the course, learners will have the ability to integrate qualitative methods into their existing workflows, improving how they approach decision-making and resource management in dynamic environments.
Case Studies in Personalized Medicine
Vanderbilt University (via Coursera)
Learn how advances in biomedicine hold the potential to revolutionize drug development, drug treatments, and disease prevention: where are we now, and what does the future hold? This course will present short primers in genetics and mechanisms underlying variability in drug responses. A series of case studies will be used to illustrate principles of how genetics are being brought to bear on refining diagnoses and on personalizing treatment in rare and common diseases. The ethical and operational issues around how to implement large scale genomic sequencing in clinical practice will be addressed. After completing this course, learners will understand 1. The ways in which genetic variants can contribute to human disease susceptibility 2. How to choose among drug therapies based on genetic factors 3. That the functional consequences of the vast majority of genetic variants discovered by modern sequencing are unknown. This course is targeted primarily at physicians 5+ years out of training. Other healthcare providers, medical/health sciences students, and members of the public may also be interested. Course launches January 15, 2016. * The information presented in “Case Studies in Personalized Medicine” is offered for educational and informational purposes only, and should not be construed as personal medical advice. If you have questions or concerns about a medical matter, please consult your doctor or other professional healthcare provider.
AI-assisted MATLAB Programming with ChatGPT
Vanderbilt University (via Coursera)
This course explores how to leverage ChatGPT as a powerful assistant for MATLAB programming, helping learners write, debug, and optimize code more efficiently. Participants will gain hands-on experience using ChatGPT to generate MATLAB programs, analyze data, and solve engineering and scientific problems. The course covers key MATLAB concepts, AI-assisted coding strategies, and best practices for integrating ChatGPT into the development workflow. Designed for beginners and experienced users alike, this course enhances MATLAB proficiency while demonstrating the synergy between AI and computational problem-solving. By the end, learners will be able to use ChatGPT effectively to accelerate coding tasks and improve productivity in MATLAB.
Introduction to Programming with MATLAB
Vanderbilt University (via Coursera)
This course teaches computer programming to those with little to no previous experience. It uses the programming system and language called MATLAB to do so because it is easy to learn, versatile and very useful for engineers and other professionals. MATLAB is a special-purpose language that is an excellent choice for writing moderate-size programs that solve problems involving the manipulation of numbers. The design of the language makes it possible to write a powerful program in a few lines. The problems may be relatively complex, while the MATLAB programs that solve them are relatively simple: relative, that is, to the equivalent program written in a general-purpose language, such as C++ or Java. As a result, MATLAB is being used in a wide variety of domains from the natural sciences, through all disciplines of engineering, to finance, and beyond, and it is heavily used in industry. Hence, a solid background in MATLAB is an indispensable skill in today’s job market. Nevertheless, this course is not a MATLAB tutorial. It is an introductory programming course that uses MATLAB to illustrate general concepts in computer science and programming. Students who successfully complete this course will become familiar with general concepts in computer science, gain an understanding of the general concepts of programming, and obtain a solid foundation in the use of MATLAB. Students taking the course will get a MATLAB Online license free of charge for the duration of the course. The students are encouraged to consult the eBook that this course is based on. More information about these resources can be found on the Resources menu on the right.
Generative AI and Model Selection
Vanderbilt University (via Coursera)
Dive into the world of generative AI and learn how to select the right model for your needs in this practical course. You'll gain a solid understanding of how generative AI models work and compare deployment options like web APIs, hosted solutions, and local installations. By the end of this course, you will be able to: • Describe the basic architecture of generative AI models • Compare different AI model deployment options • Evaluate AI models using benchmarks and custom assessments • Troubleshoot and improve model performance • Determine when to use in-context learning vs. retrieval augmented generation Through hands-on exercises, you'll learn to evaluate models using industry benchmarks and create custom assessments for your specific use cases. You'll also master techniques to troubleshoot and enhance model performance. What sets this course apart is its focus on real-world application - you'll leave equipped to make informed decisions about AI model selection and optimization for your projects. Whether you're new to AI or looking to deepen your knowledge, this course will empower you to leverage generative AI effectively.
From Data to Decisions: Making Predictions with AI
Vanderbilt University (via Coursera)
This course provides an applied introduction to bivariate and multiple regression, focusing on how generative AI can be used as a partner to streamline analysis and enhance prediction accuracy. Students will learn how to structure research questions, run regression models using AI tools, and interpret key outputs like coefficients and R-squared values. Emphasis is placed on practical applications, with generative AI guiding both the execution of the analysis and the explanation of results. By the end of the course, students will be able to leverage AI to predict outcomes and clearly communicate data-driven insights in real-world contexts. If you have little experience with data analysis, we recommend starting with From Data to Decisions: Getting Started with AI and From Data to Decisions: Finding Patterns with AI to better prepare for this course.
Hot Topics in Criminal Justice
Vanderbilt University (via Coursera)
The American criminal justice system is in need of reform. We incarcerate too many people. We pay insufficient attention to scientific advances that can help separate out the most and least culpable and dangerous. We grant the police far too much power to use force and technological surveillance. As a way of thinking about dealing with these problems, this course examines two over-arching issues: What should we do with people who have committed crime, and how should we identify who they are? On the first issue, we will look closely at the nature and causes of mass incarceration, the death penalty, the lawfulness and usefulness of preventive detention and risk assessment, and the role of the insanity defense and neuroscience in assessing responsibility for crime. On the second issue, we will explore the laws regulating the police use of force, the growing role of technology and big data in facilitating police surveillance and detection and deterrence of crime, and the remedies for police malfeasance, including the exclusionary rule and damages actions. The overall goal is to help thinking individuals assess today’s criminal justice system and consider ways of making it better. After completing this course, participants should be able to: 1. Describe the mass incarceration problem in the United States and why it might exist; 2. Suggest ways of reducing incarceration; 3. Criticize risk assessment instruments and their use in preventive detention schemes; 4. Discuss the pros and cons of the death penalty, the exclusionary rule, and the insanity defense; 5. Analyze the relevance of neurological evidence in a criminal case; 6. Identify some of the reasons innocent people are wrongly convicted; 7. Elaborate on the role race plays at sentencing and in police use of force, stop and frisk and consent searches and 8. List the types of surveillance technology available to police and the constitutional principles that govern their use.
ChatGPT for Project Management: Insight, Planning, & Success
Vanderbilt University (via Coursera)
In "ChatGPT for Project Management: Insight, Planning, & Success," you will learn how to leverage large language models (LLMs) to enhance your project planning and strategy development. This course covers techniques for using LLMs to break down complex projects into manageable tasks, phases, goals, risks, and more. You’ll discover how to utilize AI for organizing project components into timelines, schedules, strategies, dependencies, and Gantt charts to create a cohesive plan. Explore how prompting can give you instant access to "subject matter expert" insights on any topic, and learn how to control LLM output with the template pattern for precisely formatted plans and project documents. You’ll also master the use of AI to analyze risks, assess alternative approaches, generate metrics and OKRs, and optimize your project plan. By the end of this course, you'll have the skills to integrate LLMs into your project planning process, driving insight, strategy, and success.
OpenAI GPTs: Creating Your Own Custom AI Assistants
Vanderbilt University (via Coursera)
In the era of Generative AI, the demand for personalized and specialized Generative AI assistants is skyrocketing. Large language models like GPTs have demonstrated their remarkable capabilities, but what if you could harness their power to create custom AI assistants tailored to your specific needs? Welcome to the world of custom GPTs, where you can build intelligent systems that understand your domain, speak your language, and solve your unique challenges. This cutting-edge course will guide you through the exciting journey of creating and deploying custom GPTs that cater to diverse industries and applications. Imagine having a virtual assistant that can tackle complex legal document analysis, streamline supply chain logistics, or even assist in scientific research and hypothesis generation. The possibilities are endless! Throughout the course, you'll delve into the intricacies of building GPTs that can use your documents to answer questions, patterns to create amazing human and AI interaction, and methods for customizing the tone of your GPTs. You'll learn how to design and implement rigorous testing scenarios to ensure your AI assistant's accuracy, reliability, and human-like communication abilities. Prepare to be amazed as you explore real-world examples built around a GPT for Travel and Business Expense Management. The examples show how a GPT can help users book flights, hotels, and transportation while adhering to company policies and budgets. Additionally, the GPT can help streamline expense reporting and reimbursement processes, ensuring compliance and accuracy. Whether you're a business leader, entrepreneur, developer, or educator, this course will equip you with the skills to harness the transformative potential of custom GPTs. Unlock new realms of productivity, innovation, and personalized experiences by building AI assistants that truly understand and cater to your unique needs. Enroll now and join the forefront of AI revolution, where you'll learn...
Innovative Teaching with ChatGPT
Vanderbilt University (via Coursera)
Despite what you may have heard, ChatGPT offers exciting possibilities for supporting innovative teaching and personalized education. This course provides practical techniques that any educator, from K-12 to higher education, can use to help support their teaching. No experience with ChatGPT, prompt engineering, or Generative AI is required. In this course, you will learn how to do exciting things to support your teaching and student learning, such as: 1. How to brainstorm lesson plans that integrate learner interests and needs, such as generating a lesson plan to teach fourth graders about fractions using concepts from Pokemon 2. Create interactive games and turning them into concrete educational materials that you can print, such as creating a game inspired by World Cup Soccer and creating a PDF of the necessary game pieces 3. Generating engaging class activities, such as having students design fictional characters based on vocabulary and then generating funny fill in the blank stories based on the dialog 4. Helping students think of new and innovative ways of solving problems, such as generating possible ideas for building a bridge out of paperclips and plastic bottles that could support a person 5. Generating personalized quizzes on the fly that students can use to test themselves on topics and incorporate their interests, such as creating a Geometry quiz that a student can customize on the fly to use questions based on BMX bicycle racing The techniques taught are adaptable to almost any subject and student level.
Online Games: Literature, New Media, and Narrative
Vanderbilt University (via Coursera)
Intended for both newcomers who are curious about video games and experienced gamers who want to reflect on their passion, this course will explore what happens to stories, paintings, and films when they become the basis of massively multiplayer online games. The Lord of the Rings trilogy—the novels, films, and video game—are our central example of how “remediation” transforms familiar stories as they move across media. The course is designed as a university-level English literature class—a multi-genre, multimedia tour of how literature, film, and games engage in the basic human activity of storytelling. Our journey will enable us to learn something about narrative theory, introduce us to some key topics in media studies and cover some of the history and theory of video games. It will also take us to some landmarks of romance literature, the neverending story that lies behind most fantasy games: J.R.R. Tolkien’s The Fellowship of the Ring, a bit of Edmund Spenser’s Faerie Queene, and poems by Keats, Tennyson, Browning, and others. Drawing on centuries of romance narrative conventions, the twenty-first century gaming industry has become a creative and economic powerhouse. It engages the talents of some of our brightest writers, artists, composers, computer engineers, game theorists, video producers, and marketing professionals, and in 2012, it generated an estimated $64 billion in revenue. Anyone interested in today’s culture needs to be conversant with the ways this new medium is altering our understanding of stories. Join me as we set out on an intellectual adventure, the quest to discover the cultural heritage of online games.
ChatGPT + Excel: Master AI-driven Formulas & Visualizations
Vanderbilt University (via Coursera)
Imagine if your documents—policies, procedures, or even meeting notes—could magically transform into fully functional Excel spreadsheets. What used to take hours of manual labor, deciphering complex rules, and building formulas can now be done in minutes with the help of ChatGPT. This course is your gateway to unlocking that magic, turning the impossible into the achievable. Through hands-on videos, practical assignments, and real-world analogies, you'll learn how to design, prototype, and populate Excel spreadsheets like never before. For instance, think of ChatGPT as your personal assistant who not only listens to your requests but also drafts Excel formulas, creates VBA scripts, and generates polished visualizations—all while making sure everything works perfectly through robust two-sided accuracy checks. Here’s what you’ll achieve: Transform Policies into Spreadsheets: Imagine taking a dense HR policy document and converting it into a sleek, interactive tool for tracking leave requests—all by simply chatting with ChatGPT. Prototyping on the Fly: Like sketching ideas on a napkin, ChatGPT helps you rapidly prototype Excel sheets and populate them with dummy data, giving life to your ideas in moments. Snap a picture of the inside of your pantry and have it turned into an inventory tracking system. Excel Formula Wizardry: Tame the most complex formulas with ChatGPT’s guidance, from financial models to error-proofed calculations, ensuring you can solve problems without breaking a sweat. Visualizations that Wow: Snap a picture of a graph or describe a chart, and ChatGPT will help you replicate or design it in Excel with precision and flair. Automate with VBA: Automate repetitive tasks by learning how ChatGPT can craft VBA scripts tailored to your unique needs—no programming experience required. By the end of this course, you’ll have the skills to turn everyday challenges into Excel solutions, unlocking newfound productivity and creativity. Whether ...
AI Agents and Agentic AI Architecture in Python
Vanderbilt University (via Coursera)
Master the Art of Building Intelligent Python Agents That Think, Reason, and Act Unlock the full potential of Python for creating autonomous AI agents that solve complex problems without constant human direction. In this comprehensive course on AI Agents and Agentic AI with Python & Generative AI, you'll learn how to architect sophisticated agent systems that leverage Python's robust ecosystem and industry-standard capabilities. This course takes you beyond the foundations covered in the AI Agents and Agentic AI with Python & Generative AI course to explore advanced patterns for building truly intelligent agents in Python. You'll delve into specialized techniques like self-prompting, expert personas, document-as-implementation, and multi-agent orchestration - all implemented with Python's powerful frameworks and libraries. What You'll Learn: Self-Prompting Patterns in Python: Build agents that dynamically adopt different thinking modes to handle specialized tasks, transforming unstructured data into structured formats with clean Python implementations Python-Based Expert Persona Systems: Implement consultation frameworks where agents can invoke domain experts for specialized knowledge while maintaining clean architecture Document-as-Implementation: Use Python's powerful file handling to create systems where human-readable documents become executable business logic Multi-Agent Collaboration with Python: Design sophisticated memory sharing and coordination mechanisms between specialized Python agents Progress Tracking & Planning: Implement robust planning and reflection capabilities using Python's comprehensive tooling Python Agent Safety & Trust Systems: Build transaction management and safety mechanisms that leverage Python's exception handling and security features By the end of this course, you'll be equipped to build complex, production-ready agent systems in Python that can reason across multiple domains, handle complex workflows, and safel...
Introduction to Data, Signal, and Image Analysis with MATLAB
Vanderbilt University (via Coursera)
Welcome to Introduction to Data, Signal, and Image Analysis with MATLAB! MATLAB is an extremely versatile programming language for data, signal, and image analysis tasks. This course provides an introduction on how to use MATLAB for data, signal, and image analysis. After completing the course, learners will understand how machine learning methods can be used in MATLAB for data classification and prediction; how to perform data visualization, including data visualization for high dimensional datasets; how to perform image processing and analysis methods, including image filtering and image segmentation; and how to perform common signal analysis tasks, including filter design and frequency analysis.
GPT Vision: Seeing the World through Generative AI
Vanderbilt University (via Coursera)
Imagine a world where your photos don't just capture memories, but also become intelligent assistants, helping you navigate and manage daily tasks. Welcome to "GPT Vision: Seeing the World Through Generative AI", a course designed to revolutionize how you interact with the world around you through the lens of Generative AI and photos. In this course, you will learn to how take a picture of anything and turn it into: a recipe a shopping list DIY plans to make it a plan to reorganize it a description for a social media post organized text for your notes or an email an expense report or personal budget entry This course will teach you how to harness GPT Vision's power to transform ordinary photos into problem-solving tools for your job and personal life. No experience is required, just access to GPT-4(V) Vision, which is part of the ChatGPT+ subscription. Whether it's ensuring you've ticked off every item on your grocery list or creating compelling social media posts, this course offers practical, real-world applications of Generative AI Vision technology. Social Media Mastery: Learn to create compelling descriptions for your social media photos with AI, enhancing your digital storytelling. Capture Your Brainstorming: Take a picture of notes on a marker board or napkin and watch them be turned into well-organized notes and emailed to you. DIY and Culinary Creations: Explore how to use photos for DIY home projects and cooking. Discover how to generate prompts that guide you in replicating or creating dishes from images or utilizing household items for creative DIY tasks. Data Extraction and Analysis: Gain expertise in extracting and analyzing data from images for various applications, including importing information into tools like Excel. Expense Reporting Simplified: Transform the tedious task of expense reporting by learning to read receipts and other documents through GPT Vision, streamlining your financial management. Progress Tracking: Deve...
ChatGPT + Excel: Master Data, Make Decisions, Tell Stories
Vanderbilt University (via Coursera)
Struggling to keep up with your data analysis workload? Imagine having an AI assistant that not only helps you explore your Excel data but also automates mundane tasks, uncovers insights, and crafts compelling stories—all with a few prompts. This course will take you on a journey to revolutionize your Excel skills, transforming how you analyze data, make decisions, and tell impactful stories. What You'll Learn Turn Data Chaos into Clear Insights: Use ChatGPT as your AI teammate to explore complex datasets. Quickly upload your data, describe every column, identify potential errors, and understand relationships—just like onboarding a new expert colleague. Gain clarity and avoid costly pitfalls before diving into deeper analysis. Unify Your Data in Seconds—No More Headaches: Master the art of merging data from multiple Excel sheets or CSV files. Whether you're connecting job roles with industry skills or combining employee data with payroll, ChatGPT helps identify relationships and ensures your data is cohesive—giving you a complete view without manual effort. Never Fear Data Errors Again—Debug Like a Pro: Learn how to identify and resolve inconsistencies in your data, such as jobs appearing in both high and low pay categories. Use ChatGPT to dig deeper and uncover underlying issues, like duplicated entries or mismatched pay periods, making your data analysis smoother and more reliable. Say Goodbye to Tedious Data Extraction—Automate with AI: Discover how ChatGPT can automate extracting structured datasets from unformatted information. Whether it’s copying LinkedIn posts or pulling details from messy text, generative AI speeds up data preparation, turning raw material into ready-to-analyze formats in seconds. Transform Your Data into Stories That Captivate and Inspire: Elevate your presentations by using ChatGPT to craft compelling narratives from your data. Learn how to highlight key statistics and make them relatable to your audience. Develop engaging...
Building HTTP APIs with Spring
Vanderbilt University (via Coursera)
Unlock the power of building HTTP APIs with Spring, one of the most versatile and widely-used Java frameworks, in this comprehensive course tailored for both beginners and seasoned developers. Dive deep into building robust, scalable, and secure HTTP APIs from scratch and gain mastery over RESTful services with Spring Boot. What You'll Learn: Foundational Concepts: Understand the principles of REST and the significance of stateless APIs. Spring Boot Mastery: Kickstart your applications and reduce the boilerplate with Spring Boot. Dive into data access, security configurations, and more. Data Persistence: Integrate with databases using Spring Data JPA and discover the magic of CRUD operations without writing SQL. Security: Safeguard your APIs with Spring Security, implementing authentication and authorization mechanisms. Testing: Ensure your APIs stand the test of time with unit, integration, and end-to-end testing strategies. Who Should Enroll: Students should have a solid understanding of coding in Java.
AI Agents in Typescript/Javascript with Generative AI
Vanderbilt University (via Coursera)
AI Agents Are the Next Leap in Software. Learn to Build Them in TypeScript. AI agents aren't passive tools. They think, act, and solve problems—without waiting for instructions. That's the future of software. And in this course, you'll learn how to build it. Frameworks come and go. Principles last. This course cuts through the noise to teach you how AI agents really work—using TypeScript and JavaScript. Forget tutorials on trendy APIs that'll be dead by next quarter. You'll learn to build AI agents from the ground up. No fluff. No shortcuts. Just the core architecture that powers intelligent systems—knowledge that stays useful no matter how fast the landscape shifts. In this course, you will: Master TypeScript-based agent architectural fundamentals - Understand the core GAME components (Goals, Actions, Memory, Environment) that make AI agents tick and how they work together in a cohesive TypeScript system Leverage TypeScript's strengths for efficient agent development - Use TypeScript's type system, decorators, and modern JavaScript features to create robust, maintainable agent frameworks with excellent developer experience and type safety Rapidly prototype and implement TypeScript agents - Learn techniques to quickly design agent capabilities with prompt engineering before writing a single line of code, then efficiently translate your designs into working TypeScript implementations Connect TypeScript AI agents to real-world systems - Build agents that can interact with file systems, APIs, databases, and other external services using Node.js and the rich npm ecosystem Create TypeScript-powered tool-using AI assistants - Develop agents that can analyze files, manage data, and automate complex workflows by combining LLM reasoning with TypeScript's extensive libraries and functionality Build TypeScript developer productivity agents - Create specialized agents that help you write code, generate tests, and produce documentation to accelerate your so...
ChatGPT + Zapier: From Email Inbox to Excel Spreadsheet
Vanderbilt University (via Coursera)
Unlock the power of automation with ChatGPT + Zapier: From Email Inbox to Excel Spreadsheet! This hands-on course teaches you how to streamline workflows by extracting valuable information from your email inbox and effortlessly organizing it into spreadsheets. Whether you want to track expenses, log action items, collect customer reviews, or manage follow-ups, this course gives you the skills to automate tedious tasks and turn unstructured email content into structured data. Imagine transforming your Gmail inbox—or any other email provider supported by Zapier—into a dynamic source of insights. Learn how to automate data extraction and integration with thousands of popular apps in Zapier, such as Salesforce, Office365, HubSpot, Notion, and more. With detailed, step-by-step guidance, you’ll create “Zaps” that connect email providers, ChatGPT, and various apps to build seamless, automated workflows. Each lesson builds your automation skills, from setting up your data destinations and labeling emails, to configuring Zapier actions and leveraging ChatGPT’s natural language processing capabilities to extract actionable information. What You’ll Learn: • Automate Your Data Collection: Build Zaps that automatically extract key information from labeled emails and store it in tools like Google Sheets. • Customize Prompts for ChatGPT: Master the art of prompt engineering to extract structured data like dates, vendors, amounts, and categories from email bodies. • Use Code by Zapier to Process Data: Add custom JavaScript to parse ChatGPT’s responses and format them for various app integrations. • Expand and Tailor Your Automation: Clone and customize your Zap workflows to track different types of information, such as project tasks, customer feedback, or event dates. Key Course Highlights: • From Email to Apps in Minutes: Quickly set up Zaps that move data from your inbox into Google Sheets, freeing up time and reducing manual data entry. • Hands-On Projects: Follow a...
Generative AI & AI Agent Organizational Strategy for Leaders
Vanderbilt University (via Coursera)
Forget everything you know about traditional artificial intelligence. Generative AI and Agentic AI aren’t just new tools—they’re a new form of cognitive labor. They don’t simply analyze information; they take action, execute multi-step workflows, and deliver outcomes that once required teams of experts. From diagnosing equipment failures with a single photo to autonomously building full-stack software applications in minutes, AI labor is redefining what organizations can achieve. This course shows leaders how to harness it strategically—before their competitors do. In Generative AI & AI Agent Organizational Strategy for Leaders, you’ll learn why AI is no longer an IT initiative, a technical experiment, or a siloed innovation project. It is now a strategic workforce capability—a new category of labor that every employee can deploy through conversation, creativity, and problem-solving. You’ll discover how AI agents unlock 100x–1000x productivity gains, why vendor-locked “AI add-ons” can cripple your innovation capacity, and how organizations must rethink procurement, capability development, and labor strategy to stay competitive. You’ll see firsthand how simple inputs—a photo, a document, a spreadsheet, a menu, a policy—can instantly become powerful AI-driven systems that perform tasks previously impossible or cost-prohibitive. Leaders will explore how employees at every level can use AI to enhance decision-making, compress time, and scale expertise, not replace roles. The real competitive advantage comes from teaching your workforce to think in conversations, design AI workflows, and orchestrate these new digital laborers effectively. By the end of this course, you won’t just understand what agentic AI is—you’ll know how to operationalize it. You’ll learn how to: • Build an organizational AI labor strategy that attracts the “best and brightest” models and keeps you vendor-independent. • Identify high-value starting points using simple but transformation...
From Data to Decisions: Getting Started with AI
Vanderbilt University (via Coursera)
This course is intended for individuals who'd like to work with data from their organization but don't know where to start. We'll combine generative AI and your insights to structure research questions, understand the variables in your dataset, and begin describing the data for the purpose of generating insights into better decisions. After taking this course, learners will know how to identify the outcomes and predictors in a dataset and how to summarize different types of variables in a dataset using generative AI.
Generative AI Cybersecurity & Privacy for Leaders: A Primer
Vanderbilt University (via Coursera)
Are you ready to lead your organization into the future of cybersecurity while safeguarding privacy in an increasingly AI-driven world? This primer provides an essential foundation in generative AI, exploring its transformative potential and the specific cybersecurity and privacy risks it introduces. Learn to embrace AI’s capabilities while maintaining trust, compliance, and security in your organization. What You'll Learn: Safeguard Organizational Privacy: This primer will help you understand the privacy implications of AI systems and the risks posed by data fusion across platforms. Address Emerging AI-Specific Threats: Develop a clear understanding of vulnerabilities like prompt injection, deepfakes, AI-enhanced phishing, and adversarial text in AI deployments. Build Confidence in AI Adoption: Gain the foundational tools and techniques to implement secure environments for AI development and responsible usage. Who Is This Course For? Cybersecurity and Privacy Leaders: Seeking a primer to harness AI while preserving organizational integrity. IT Professionals: Interested in responsibly implementing AI within technical infrastructures. Business Executives: Looking for a foundational understanding of AI integration without compromising compliance or ethics. Policy Makers: Aspiring to shape legislation around AI and privacy with a deep technical primer. Why Take This Course? Generative AI offers unmatched opportunities to enhance security and privacy, but it also brings novel challenges. From adversarial risks to complex data privacy concerns, leaders need a clear and concise primer to navigate these complexities effectively. This course provides the essential knowledge and skills to balance innovation with protection. By the end, you’ll be empowered to lead AI initiatives that drive progress while mitigating the unique cybersecurity risks posed by generative AI. With this primer, you’ll confidently lay the groundwork for safe and responsible AI...
Microservice Architectures
Vanderbilt University (via Coursera)
Dive into the world of Microservices Architectures with this comprehensive course, designed to provide a clear understanding of both the theoretical and practical aspects of building scalable and robust systems. Beginning with the concept of program slicing, this course will guide you through the intricacies of Microservices, contrasting them against monolithic systems, and demonstrating the art and science behind their design, deployment, and maintenance. What You'll Learn: Program Slicing and its Relevance: Dive into the foundational concepts of program slicing, its significance in system design, and its relationship with Microservices. Monoliths vs. Microservices: Contrast the architectural styles, understanding the strengths, weaknesses, and practical differences of each approach. Decoupling and Invocation Dynamics: Grasp the intricacies of service decoupling, hidden couplings, and the complexities of service invocation within a Microservices environment. Deployment, Scalability, and Dependency Management: Delve into the challenges and consequences of adopting Microservices, focusing on deployment strategies, scalability issues, and dependency isolation. Building Resilient Systems: Explore client-side load balancing, circuit breakers, fallback strategies, and other resilience techniques to ensure system stability and robustness. Who Should Enroll: Students should have intermediate Java programming experience.
AI Agents and Agentic AI with Python & Generative AI
Vanderbilt University (via Coursera)
AI Agents Are the Next Leap in Software. Learn to Build Them in Python. AI agents aren't passive tools. They think, act, and solve problems—without waiting for instructions. That's the future of software. And in this course, you'll learn how to build it. Frameworks come and go. Principles last. This course cuts through the noise to teach you how AI agents really work—using Python, the leading language for AI development. Forget tutorials on trendy APIs that'll be dead by next quarter. You'll learn to build AI agents from the ground up. No fluff. No shortcuts. Just the core architecture that powers intelligent systems—knowledge that stays useful no matter how fast the landscape shifts. In this course, you will: Master Python-based agent architectural fundamentals - Understand the core GAME components (Goals, Actions, Memory, Environment) that make AI agents tick and how they work together in a cohesive Python system Leverage Python's strengths for efficient agent development - Use Python's dynamic typing, decorators, and metaprogramming to create flexible, maintainable agent frameworks with minimal boilerplate code Rapidly prototype and implement Python agents - Learn techniques to quickly design Python agent capabilities with prompt engineering before writing a single line of code, then efficiently translate your designs into working Python implementations Connect Python AI agents to real-world systems - Build Python agents that can interact with file systems, APIs, and other external services Create Python-powered tool-using AI assistants - Develop Python agents that can analyze files, manage data, and automate complex workflows by combining LLM reasoning with Python's extensive libraries and ecosystem Build Python developer productivity agents - Create specialized Python agents that help you write code, generate tests, and produce documentation to accelerate your software development process Why Principles Matter More Than Frameworks The AI...
Leading Innovation in Arts and Culture
Vanderbilt University (via Coursera)
Developed by David Owens at Vanderbilt University and customized for the cultural sector with National Arts Strategies, this course is designed to help arts and culture leaders create an environment where new ideas are constantly created, shared, evaluated and the best ones are successfully put to work. One of the toughest challenges for any leader is getting traction for new ideas. Winning support can be a struggle. As a result, powerful new ideas often get stuck. This is especially true in the cultural sector. People involved in arts and culture often have little time and even less money for experimentation and risks. This course will help those in the performing arts, museums, zoos, libraries and other cultural organizations build environments where new management and program ideas flourish. Leading Innovation in Arts & Culture will teach you how to make an "innovation strategy" a fundamental component of your organization's overall strategy. In this seminar you will learn to: Analyze constraints on innovation in your organization, foresee obstacles and opportunities, and develop a shared vision Develop a process to manage the demands of multiple stakeholders, shifting priorities and the uncertainty inherent in new initiatives Create a culture for innovation and risk-taking that generates new perspectives and challenges existing practice Create a strong customer focus within your organization that anticipates customer needs National Arts Strategies worked with David Owens to customize this course for those working in the cultural sector. They based their work on David Owens’ Leading Strategic Innovation in Organizations course. This highly interactive 8-week course will engage you in a series of class discussions and exercises.
Engineering Maintainable Android Apps
Vanderbilt University (via Coursera)
Engineering Maintainable Android Apps, which is a 4 week MOOC that shows by example various methods for engineering maintainable Android apps, including test-driven development methods and how to develop/run unit tests using JUnit and Robotium (or equivalent automated testing frameworks for Android), as well as how to successfully apply common Java/Android software patterns to improve the extensibility and clarity of Android apps. Students will work on the appropriate automated unit quizzes, based on the material covered in the lecture videos. These lessons will demonstrate the benefits of good software engineering practices that are targeted at creating maintainable code for mobile apps. There will be roughly 3-4 hours of student engagement time per week, including video lectures, and quizzes. The ordering of the modules within the course is designed to be flexible. In particular, students can watch the videos in whatever order suits their experience and needs, e.g., they may want to watch the unit testing videos prior to the software pattern videos if they prefer to learn about unit testing first.
Understanding the Music Business: What is Music Worth?
Vanderbilt University (via Coursera)
This course will examine the music industry in the United States, with the unique perspective gained by Vanderbilt University’s location in Nashville, TN. Nashville is a major center of music in the United States, and the music created here has a global reach, particularly in the country, rock, pop, singer-songwriter, and Americana genres. However, students will learn that the basic principles of recording, marketing, copyright, licensing, and live performance are the same, regardless of musical style or genre. The music business is one of the most rapidly changing industries in the US today. It is also an industry filled with contradiction, and media headlines and anecdotal stories often add to the confusion. Here are just a few statements paraphrased from recent news stories: The music business has collapsed Demand for music is expanding at the greatest rate in history Historic recording studios are closing at an alarming rate More people are making recordings than ever before Musicians usually lose money touring Musicians usually make money touring Major artist pulls songs off streaming services because they don’t pay fairly Major artist makes a fortune from streaming services People won’t buy records anymore Vinyl record sales are soaring This course will attempt to make sense of these seemingly contradictory trends and data, outline the basic structure and mechanisms of today’s music industry, and encourage students to think critically and entrepreneurially about the future of music. Leaders from various areas of the music business will lend their perspectives through in-depth interviews, and footage from a recording session will give learners a behind the scenes look at how a song goes from the spark of an idea hummed into a cell phone to a finished recording. Participants will grapple with questions about art and commerce which are both timeless and crucially important today, and will emerge from this course with tools allowing t...