Northeastern University
Public University • US
Showing 111 courses from Northeastern University
Data Warehousing and Integration Part 1
Northeastern University (via Coursera)
This course will cover various topics in data engineering in support of decision support systems, data analytics, data mining, machine learning, and artificial intelligence. You will study on-premises data warehouse architecture, dimensional modeling of data warehouses, Extract-Transform-Load (ETL) integration from source systems to data warehouse, On-line Analytical Processing (OLAP) systems, and the evolving world of data quality and data governance. It offers you an opportunity to design, develop and maintain cloud-based data pipelines. Both on-premises and cloud-based platforms will be used to illustrate and implement data engineering techniques using operational and analytical data warehouses.
Agile Software Development Part 2
Northeastern University (via Coursera)
This course delves into Agile software development, offering students a practical understanding of the software development life cycle (SDLC) with a strong emphasis on Agile methodologies. Throughout the program, participants will explore the technical, cultural, and social aspects of agility, empowering them to navigate the complexities of modern software development.
Healthcare Information Design and Visualizations
Northeastern University (via Coursera)
Introduces processes and design principles for creating meaningful displays of information that support effective business decision-making. Studies how to collect and process data; create visualizations (both static and interactive); and use them to provide insight into a problem, situation, or opportunity. Introduces methods to critique visualizations along with ways to answer the elusive question: “What makes a visualization effective?” Discusses the challenges of making data understandable across a wide range of audiences. Introduces the fundamentals of communication required for effective data storytelling. Other topics may include ethical uses of information displays, storytelling, infographics, and immersive visualizations. Offers students an opportunity to use one or more software tools. Looking for a for-credit offering of this course? Take this course as a 3-credit For-Credit, Non-Degree course and get a taste Northeastern University's world-class online programs without the commitment of a full degree. Take the course as a standalone for credit or stack the credits into eligible degree and certificate programs. Learn more and register: https://online.northeastern.edu/courses/information-visuals-and-dashboards-for-business
Healthcare Financial Management Fundamentals
Northeastern University (via Coursera)
This course is the continuation of "Intro to Finance in Healthcare." If you have not yet taken the introductory course, it is recommended that you complete that course prior to this course. The foundational knowledge is carried through in this deeper dive into financial management in healthcare. In this course, you will continue to explore concepts and topics related to accounting and finance basics for healthcare organizations. You will learn how to read, interpret, and use a financial statement in order to understand the financial health of an organization. You will explore long-term financing and learn about the types of debt available to healthcare organizations. You will also be introduced to financial planning and analysis and how to best assess the financial performance of a company. You will be asked to put yourself in the position of a financial officer within a healthcare organization as you explore the complexities and challenges healthcare organizations face when managing healthcare financial decisions. Throughout this course, you will be given the opportunity to evaluate your understanding through engagement in a course project, discussions, and through completion of content quizzes along the way.
Data Warehousing Essentials for Analytics and AI Support
Northeastern University (via Coursera)
This course will cover various topics in Data Engineering in support of decision support systems, data analytics, data mining, machine learning, and artificial intelligence. You will study on-premises data warehouse architecture, and dimensional modeling of data warehouses.
Foundations for Data Analytics Part 2
Northeastern University (via Coursera)
This course offers students an opportunity to learn fundamentals of computation required to understand and analyze real world data. The course helps students to work with modern data structures, apply data cleaning and data wrangling operations. The course covers conceptual and practical applications of probability and distribution, cluster analysis, text analysis and time series analysis. This is Part 2 of 2.
Data Warehousing and Integration Part 2
Northeastern University (via Coursera)
Covers various topics in Data Engineering in support of decision support systems, data analytics, data mining, machine learning, and artificial intelligence. Studies on-premises data warehouse architecture, dimensional modeling of data warehouses, Extract-Transform-Load (ETL) integration from source systems to data warehouse, On-line Analytical Processing (OLAP) systems, and the evolving world of data quality and data governance. Offers students an opportunity to design, develop and maintain cloud-based data pipelines. Both on-premises and cloud-based platforms will be used to illustrate and implement Data Engineering techniques using operational and analytical data warehouses.
Agile Software Development Part 1
Northeastern University (via Coursera)
This course delves into Agile software development, offering students a practical understanding of the software development life cycle (SDLC) with a strong emphasis on Agile methodologies. Throughout the program, participants will explore the technical, cultural, and social aspects of agility, empowering them to navigate the complexities of modern software development.
Engineering Probability and Statistics Part 2
Northeastern University (via Coursera)
Engineering Probability and Statistics Part 2 covers the principles of statistical inference, including sampling distributions, confidence intervals, hypothesis testing, and analysis of variance (ANOVA) for comparing means across multiple groups. Through a structured yet flexible approach, students will gain the skills needed to apply statistical reasoning to engineering problems and communicate data-driven insights effectively. This course is designed to support continuous engagement and steady progress throughout the term.
User Experience Design and Testing Part 1
Northeastern University (via Coursera)
This course will offer you an opportunity to learn fundamentals UX design and design principles. The concepts in this course will prepare you to work with modern design software, apply design techniques, and how to use common design software. Throughout this course experience, you will learn about design strategies, user research, and design planes. Throughout your time in this course, you will be given opportunities to check your understanding of course material, as well as engage in quizzes to reflect on all the concepts you have explored within each module. By the end of this part 1 course on user experience design and testing, you will have a foundational understanding of designing for the user experience and practical applications.
Foundations for Data Analytics Part 1
Northeastern University (via Coursera)
This course offers students an opportunity to learn fundamentals of computation required to understand and analyze real world data. The course helps students to work with modern data structures, apply data cleaning and data wrangling operations. The course covers conceptual and practical applications of probability and distribution, cluster analysis, text analysis and time series analysis. This course is Part 1 of 2.
Designing Engaging Dashboards for Healthcare Analytics
Northeastern University (via Coursera)
Introduces processes and design principles for creating meaningful displays of information that support effective business decision-making. Studies how to collect and process data; create visualizations (both static and interactive); and use them to provide insight into a problem, situation, or opportunity. Introduces methods to critique visualizations along with ways to answer the elusive question: “What makes a visualization effective?” Discusses the challenges of making data understandable across a wide range of audiences. Introduces the fundamentals of communication required for effective data storytelling. Other topics may include ethical uses of information displays, storytelling, infographics, immersive visualizations, and good use of data dashboards. Offers students an opportunity to use one or more software tools.
Intro to Improving the Patient Experience Through Analytics
Northeastern University (via Coursera)
This course is best suited for individuals currently in the healthcare sector, as a provider, payer, or administrator. Individuals pursuing a career change to the healthcare sector may also be interested in this course. In this course, you will have an opportunity to explore concepts and topics related to improving the patient experience and reducing pain points in healthcare processes through analytic and decision support frameworks. After learning about the problems facing patients in today's health system, you will survey the kind of data that is used to make effective decision support choices, following up with information on how to use the data to predict outcomes. Throughout this course, you will be given the opportunity to apply the course concepts to operational improvements in your own organization.
Data-Driven Systems: DBMS, SQL & Data Modeling
Northeastern University (via Coursera)
In the Data-Driven Systems: DBMS, SQL & Data Modeling course, you will gain an essential foundation in database theory and skills, exploring key concepts and architecture within a data-centric system context. You will acquire valuable knowledge and skills in managing, manipulating, and analyzing large datasets, with an emphasis on both relational and NoSQL databases.
Computation and Visualization for Analytics Part 2
Northeastern University (via Coursera)
Offers students an opportunity to learn how to use visualization tools and techniques for data exploration, knowledge discovery, data storytelling, and decision making in engineering, healthcare operations, manufacturing, and related applications. Covers basics of Python and R for data mining and visualization. Introduces students to static and interactive visualization charts and techniques that reveal information, patterns, interactions, and comparisons by focusing on details such as color encoding, shape selection, spatial layout, and annotation.
Data Structures & Algos: Software Development Skills
Northeastern University (via Coursera)
This course will guide you through the essential principles of algorithms and their significance in computational problem-solving. You'll begin by exploring what an algorithm is, its core characteristics, and how it applies to real-world scenarios—from simple everyday tasks to complex computing challenges. As you progress, you will learn about the critical role algorithms play in improving efficiency and scalability across various fields. We’ll break down key concepts such as algorithmic complexity, helping you evaluate the efficiency of different approaches, which will ultimately guide your decision-making.
Basic Programming in Python I
Northeastern University (via Coursera)
This hands-on Python programming course offers students an opportunity to obtain proficiency in the core concepts of Python as well as the programming skills for building applications using tools from various task-specific Python libraries. The course covers important topics in computer science and information systems such as data types, reading and writing to standard IO, using operators, controlling the flow of execution, using functions, reading and writing Python source code files, basic object-oriented programming concepts, and more. You will be introduced to preliminary topics in data science and explore the process of building a web application using Python. You will complete hands-on programming tasks using your creativity and learn how to apply Python to resolve real-world problems.
Intro to Managing Ethics in the Workplace & Marketplace
Northeastern University (via Coursera)
Are you seeking practical guidance for improved decision making in business situations involving critical ethical issues? Are you looking to participate in creative and constructive thinking and learning around these topics? This course is designed to help you. Flawed ethical reasoning has interfered with patient care, undermined shareholder value, eroded public trust, distanced employees and destroyed careers. Using a combination of didactic instruction and a series of case studies, readings, and field study experiences, the course will actively engage you in a timely, relevant, and challenging fashion.
Applied Natural Language Processing in Engineering Part 1
Northeastern University (via Coursera)
Welcome to this course on applied natural language processing in engineering. This course is designed to provide you with an in-depth understanding of NLP, a pivotal area of artificial intelligence that empowers computers to comprehend, interpret, and generate human language. Throughout this course, you will explore a wide range of topics, from fundamental NLP tasks like text classification and Named Entity Recognition (NER) to advanced techniques in neural machine translation and optimization methods critical for machine learning. We will delve into the complexities of teaching language to machines, addressing challenges like ambiguity, grammar, and cultural nuances. By the end of this part 1 course, you will have a foundational understanding of how modern NLP systems work - particularly those involving machine learning and deep learning. These topics will equip you to build, analyze and improve NLP systems across many applications.
Planning and Managing Information Systems Development Part 2
Northeastern University (via Coursera)
This course will provide an overview of the most popular information systems needs’ assessment methodologies including portfolio analysis, stage assessment, business systems planning. Topics include utilities Information Systems strategic plan prioritization techniques of business goal alignment, architectural compatibility, and cost/benefit and risk analysis demonstrating how businesses match needs to budgetary constraints. This course will describe and evaluate options for the placement of the Information Systems function within an organization and a variety of methods to manage the function.
Data Management and Database Design Part 1
Northeastern University (via Coursera)
In the Data Management and Database Design Part 1 course, you will gain an essential foundation in database theory and skills, exploring fundamental concepts and basic database structures. You will acquire valuable knowledge and skills in understanding, querying, and working with core database systems, with an emphasis on both relational and NoSQL database fundamentals.
Applied Natural Language Processing in Engineering Part 2
Northeastern University (via Coursera)
This course is best suited for software engineers, data scientists, and graduate students in computer science or engineering fields who wish to develop expertise in building and deploying natural language processing systems to solve real-world language understanding challenges. You will master core NLP tasks such as Part-of-Speech tagging, Named Entity Recognition, sentiment analysis, and Neural Machine Translation while implementing various neural architectures from Recurrent Neural Networks and bidirectional RNNs to Conditional Random Fields and state-of-the-art transformer models. The course emphasizes practical application through extensive laboratory work and projects, where you will develop complete NLP pipelines using frameworks like PyTorch and Hugging Face, learning to preprocess data, train models, and evaluate performance using industry-standard metrics. By the end of the course, you will be equipped with both theoretical understanding and practical skills to design, implement, and optimize NLP solutions for real-world engineering applications, from chatbots and translation systems to information extraction and text analysis tools. The curriculum culminates in a comprehensive capstone project where you will apply multiple techniques learned throughout the course to solve a complex language processing challenge. You will be equipped with both theoretical knowledge to tackle complex language processing problems in industry settings, enabling you to build production-ready NLP applications that can understand, interpret, and generate human language effectively.
Basic Programming in Python II
Northeastern University (via Coursera)
This hands-on Python programming course offers students an opportunity to obtain proficiency in the core concepts of Python as well as the programming skills for building applications using tools from various task-specific Python libraries. The course covers important topics in computer science and information systems such as data types, reading and writing to standard IO, using operators, controlling the flow of execution, using functions, reading and writing Python source code files, basic object-oriented programming concepts, and more. You will be introduced to preliminary topics in data science and explore the process of building a web application using Python. You will complete hands-on programming tasks using your creativity and learn how to apply Python to resolve real-world problems.
AI Innovation in Healthcare
Northeastern University (via Coursera)
AI is transforming healthcare, offering new ways to improve diagnostics, personalize treatment, and streamline clinical workflows. In this course, you will explore why AI is essential in modern healthcare, examining how data—ranging from electronic health records to medical imaging—drives AI-powered solutions. You’ll be introduced to key data exploration techniques used to uncover patterns and insights in healthcare data, as well as foundational AI approaches, including traditional rule-based systems, predictive analytics, and emerging generative AI models. We’ll also discuss the challenges of AI in healthcare, including biases, ethical concerns, and AI ‘hallucinations’—instances where AI generates misleading or incorrect information. By the end of this course, you’ll have a solid understanding of AI’s capabilities and limitations in healthcare and be prepared to critically assess its role in patient care and decision-making.
Foundations of Statistical Learning & Algorithms
Northeastern University (via Coursera)
This course covers linear algebra, probability, and optimization. It begins with systems of equations, matrix operations, vector spaces, and eigenvalues. Advanced topics include Cholesky and singular value decomposition. Probability modules address Bayes' theorem, Gaussian distribution, and inference techniques. The course concludes with model selection methods and an introduction to optimization.
Data Privacy Fundamentals
Northeastern University (via Coursera)
This course is designed to introduce data privacy to a wide audience and help each participant see how data privacy has evolved as a compelling concern to public and private organizations as well as individuals. In this course, you will hear from legal and technical experts and practitioners who encounter data privacy issues daily. This course will review theories of data privacy as well as data privacy in the context of social media and artificial intelligence. It will also explore data privacy issues in journalism, surveillance, new technologies like facial recognition and biometrics. Completion of the course will enable the participant to be eligible for CPE credit.
Machine Learning for Engineers: Algorithms and Applications
Northeastern University (via Coursera)
This course covers practical algorithms and the theory for machine learning from a variety of perspectives. Topics include supervised learning (generative, discriminative learning, parametric, non-parametric learning, deep neural networks, support vector Machines), unsupervised learning (clustering, dimensionality reduction, kernel methods). The course will also discuss recent applications of machine learning, such as computer vision, data mining, natural language processing, speech recognition and robotics. Students will learn the implementation of selected machine learning algorithms via python and PyTorch.
Health Informatics for Healthcare Professionals
Northeastern University (via Coursera)
This course is best suited for individuals currently in the healthcare sector, as a provider, payer, or administrator. Individuals pursuing a career change to the healthcare sector may also be interested in this course. In this course, you will have an opportunity to explore concepts and topics related to the design and management of health information systems. After an introduction to the history and current status of information systems in healthcare, you will then explore the areas of information architecture, administrative and clinical applications, information retrieval, decision support systems, the electronic health record, key health information systems and standards. Throughout this course, you will be given the opportunity to evaluate your understanding through engagement in course discussions, application of course concepts to a course assignment, and through completion of content quizzes along the way.
Future Healthcare Payment Models
Northeastern University (via Coursera)
This course will review the drivers of healthcare cost and solutions that have been proposed to address cost, quality and value of health care. Many point blame for high costs on payment models that pay healthcare providers for every service they provide to patients, essentially paying more for volume and service intensity. This is called a Fee for Service (FFS) payment model. Some solutions, arguably the more sustainable solutions, are the combined strategies of new payment models, care management, insurance plan designs, consumer engagement tools, and technology. Using that information we will explore various situations, showcasing coordinated care and payment strategies that can be implemented to improve patient health and the cost of delivery of healthcare services. By the end of this course, the learner should be able to: 1. Identify the drivers and trends of healthcare spending from the perspective of various stakeholders, including medical providers, insurers, government and private purchasers and payments 2. Critically assess the impact of strategic and financial approaches that have been put in place by the ACA and the various modifications. 3. Evaluate how healthcare payment models currently work and the new direction that value-based payment is taking. 4.Identify how financial and non-financial metrics can be appropriately combined to improve a healthcare stakeholders’ value proposition.
Understanding & Influencing Workplace Behavior
Northeastern University (via Coursera)
Examines today’s evolving environment, in which effective utilization of human resources is a source of competitive advantage. To maximize the contribution of organizational members, managers must be able to understand, diagnose, and influence workplace behavior in the context of change. Topics include management of cross-functional teams and boundaryless organizations. Emphasis is on the role of corporate culture and distributed leadership.
Data Management for Analytics Part 1
Northeastern University (via Coursera)
This course will offer you an opportunity to learn the fundamental concepts and emerging technologies in database design and modeling and database systems. It presents a balanced theory-practice focus and covers entity relationship model and UML model, relational model, and relational databases. By the end of this part 1 course on data analytics, you will have a foundational understanding of the theory and applications of database management to support data analytics, data mining, machine learning, and artificial intelligence.
Engineering Project Management Part 1
Northeastern University (via Coursera)
Examines the theory and practice of managing projects. Explores human, mathematical, entrepreneurial, managerial, and engineering aspects of project management. The systems development life cycle is the framework for the course. Addresses needs analysis, requirements definition, design, and implementation in the context of project management. Introduces mathematical and software tools for planning, monitoring, and controlling projects.
Business Application of Machine Learning and Artificial Intelligence in Healthcare
Northeastern University (via Coursera)
The future of healthcare is becoming dependent on our ability to integrate Machine Learning and Artificial Intelligence into our organizations. But it is not enough to recognize the opportunities of AI; we as leaders in the healthcare industry have to first determine the best use for these applications ensuring that we focus our investment on solving problems that impact the bottom line. Throughout these four modules we will examine the use of decision support, journey mapping, predictive analytics, and embedding Machine Learning and Artificial Intelligence into the healthcare industry. By the end of this course you will be able to: 1. Determine the factors involved in decision support that can improve business performance across the provider/payer ecosystem. 2. Identify opportunities for business applications in healthcare by applying journey mapping and pain point analysis in a real world context. 3. Identify differences in methods and techniques in order to appropriately apply to pain points using case studies. 4. Critically assess the opportunities to leverage decision support in adapting to trends in the industry.
Data Analytics Engineering: Probability & Techniques
Northeastern University (via Coursera)
This course offers students an opportunity to learn fundamentals of computation required to understand and analyze real world data. The course helps students to work with modern data structures, apply data cleaning and data wrangling operations. The course covers conceptual and practical applications of probability and distribution, cluster analysis, text analysis and time series analysis.
Responsible and Ethical AI
Northeastern University (via Coursera)
In this course, we will investigate the ethical challenges in Artificial Intelligence (AI) systems. The focus of this course is on preparing students with the knowledge and practical approaches necessary in designing reliable and ethical AI systems that are responsible and trustworthy. Key topics covered include: • Bias and Fairness in AI and Machine Learning • Nature of data privacy and AI Risks • Understanding AI regulations. • Frameworks for building truly trustworthy and responsible AI. There are 2 hands-on labs in this course. You need knowledge of python and basics of AI model development.
Healthcare Consumerism and Implication for Care Delivery
Northeastern University (via Coursera)
In this course we will examine the changing role of the consumer in healthcare. Consumers are asking for more accountability in how healthcare is delivered and paid for. Healthcare professionals must make sure that they are delivering high quality, personalized care. Some of the topics we'll cover are: the healthcare ecosystem, new technologies in healthcare, the development of new payment models, change management in healthcare, data analytics. By the end of this course, you will be able to: 1. Explain the new role of consumers in healthcare delivery in order to respond to the demands in this changing industry 2. Identify the key players in the healthcare ecosystem 3. Describe how the healthcare system operates and its impact on consumer-driven healthcare. 4. Articulate the challenges facing consumers and providers in order to find potential solutions for these challenges.
Web Design and User Experience Engineering Part 2
Northeastern University (via Coursera)
Introduces the fundamentals of developing web user-interface/user-experience (UI/UX). This course will focus on core concepts and best practices involved in developing web applications that are not tied to specific libraries or frameworks. Topics include HTML, CSS, Javascript, React, and basic accessibility (a11y).
Agile Dev Practices: SDLC & Project Management
Northeastern University (via Coursera)
In this course, you will learn about Agile software development, offering a practical understanding of the software development life cycle (SDLC) with a strong emphasis on Agile methodologies.
Analytics in Healthcare Management and Administration
Northeastern University (via Coursera)
This course is the continuation of Healthcare Analytics Essentials . If you have not yet taken the Healthcare Analytics Essentials course, it is recommended that you complete that course prior to this course. The foundational knowledge to support the project are carried through in this deeper dive into using healthcare analytics in management and administration. This course provides you the opportunity to learn about how business analytics can improve the health organization performance and ways to identify and address issues that affect patient care. You will explore the components of care continuity, the strategies used to achieve continuity, and the characteristics of patient-centeredness. You will also review the structure and value of the randomized controlled trial and the need for decision-making at the individual level. Finally, you will learn about systems in healthcare, the 6Cs of systemness, and the five common properties of complex systems and the framework to create change.
Navigating Ethics in the Healthcare Workplace & Marketplace
Northeastern University (via Coursera)
This course seeks to stimulate creative thinking and learning for you as a working professionals while offering practical guidance for improved decision-making in both common and novel ethical business situations. You will look at navigating ethics as related to issues associated with the governance of medical organizations, end-of-life care, and an array of especially difficult issues in the healthcare environment. We hope this course will help you re-examine your own thoughts and ideas about ethics and reflect on whether the course content has enlarged your sense of moral suasion.
Engineering Project Management Part 2
Northeastern University (via Coursera)
Examines the theory and practice of managing projects. Explores human, mathematical, entrepreneurial, managerial, and engineering aspects of project management. The systems development life cycle is the framework for the course. Addresses needs analysis, requirements definition, design, and implementation in the context of project management. Introduces mathematical and software tools for planning, monitoring, and controlling projects.
Fundamentals of Integrated Brand Promotion
Northeastern University (via Coursera)
This course explores integrated brand promotion (IBP) in today's complex marketing landscape. Beginning with foundational concepts of advertising and IBP within the marketing ecosystem, learners will gain insight into the intricate relationships that drive this trillion-dollar industry. Through exposure to branding fundamentals, learners will explore brand elements, architecture, positioning, and differentiation strategies that contribute to brand recognition and consumer decision-making. Key topics include strategic considerations for product and service positioning, advertising approaches, and the impactful role of data in shaping effective brand promotion strategies. The course culminates with practical applications across diverse scenarios, equipping learners with knowledge of how successful brands implement integrated promotion strategies to connect with audiences and achieve marketing objectives in an evolving digital environment. This course is best suited for individuals seeking to advance their careers through skill-building, industry application, and network expansion. Whether aiming for a promotion, transitioning to a new career, or growing one’s professional skills, learners will gain valuable insights into how they can contribute to their organizations and articulate those ideas with peers, recruiters, and other stakeholders.
Engaging in Strategic Management in Healthcare Organizations
Northeastern University (via Coursera)
This is the second part of a two-part Strategic Management for Healthcare Organizations course. The first course, "Intro to Strategic Management for Healthcare Organizations", focuses on business strategy. This second part presents and discusses analytical frameworks for making strategic decisions, drawing on different disciplines, including economics and management. You will get an understanding of how strategic decisions are made within organizations. After exploring the different levels of strategy in the first course, you will now dive into each level in greater detail. You will have the opportunity to conduct an external evaluation that examines market, environment, customer, and competitor analyses. You will get an understanding of strategic issues in healthcare organizations, including mergers and acquisitions, vertical integration, joint ventures and alliances, performance-control systems, and organizational design.
Economic Decision Making Part 1
Northeastern University (via Coursera)
Explores economic modeling and analysis techniques for selecting alternatives from potential solutions to an engineering problem. Considers measures of merit, such as present worth, annual worth, rate of return, and benefit/cost techniques. Examines recent techniques of economic analysis, especially the tools of decision-making. Explores decisions under uncertainty. Studies the causes of risk and uncertainty and examines ways to change and influence the degree of risk and uncertainty through sensitivity analysis, expectation-variance criterion, decision tree analysis, statistical decision techniques, and multiple attribute decision-making through group case studies.
Navigating Healthcare Supply Chain Operations
Northeastern University (via Coursera)
This course is the continuation of "Introduction to Healthcare Supply Chain Operations". If you have not visited the first part yet, please check it out before starting this course. If you have finished the first part of this series: Introduction to Healthcare Supply Chain Operations, you will be able to apply what you learned to your own career. The foundational knowledge and project plan from the introduction are carried through in this deeper dive into healthcare supply chain operations. In this course, you will focus on activities and functions such as inventory control, logistics, procurement, supply chain relationships, information technology systems and innovations, and response to emerging trends. It introduces various tools and techniques that enhance effective management of supply chain operations in healthcare organizations. Throughout this course, you will be given the opportunity to apply the course concepts to an operational process improvement project.
Program Structure and Algorithms Part 1
Northeastern University (via Coursera)
This course will guide you through the essential principles of algorithms and their significance in computational problem-solving. You'll begin by exploring what an algorithm is, its core characteristics, and how it applies to real-world scenarios—from simple everyday tasks to complex computing challenges. As you progress, you will learn about the critical role algorithms play in improving efficiency and scalability across various fields. We’ll break down key concepts such as algorithmic complexity, helping you evaluate the efficiency of different approaches, which will ultimately guide your decision-making.
Ethics and Governance in the Age of Generative AI
Northeastern University (via Coursera)
This course is best suited for individuals who are looking to expand their understanding of generative AI and best practices for the responsible, ethical incorporation of generative AI tools in the flow of work. This course explores the ethical and technical dimensions of developing and deploying AI models with a focused lens on generative AI. It examines the ethical and societal considerations of emerging technologies and unique challenges posed by generative AI. This course details the mechanics of genAI, and technical strategies to reduce bias. It explores the RAI principles, strategy, and governance surrounding generative AI. By the end of this course you will have a developed understanding of the nuances of the ethical and technical intricacies shaping the development and deployment of AI models, with a particular focus on generative AI.
Data Visualization with Python & R for Engineers
Northeastern University (via Coursera)
The primary objective of this course is to offer students an opportunity to learn how to use visualization tools and techniques for data exploration, knowledge discovery, data storytelling, and decision making in engineering, healthcare operations, manufacturing, and related applications. This course covers basics of data mining and visualization, and Python. It also introduces students to static visualization charts and techniques that reveal information, patterns, interactions.
Systems and Cybersecurity Fundamentals Part 1
Northeastern University (via Coursera)
This course is best suited for individuals who wish to develop expertise in cybersecurity fundamentals, including aspiring security professionals, IT administrators seeking to enhance their security knowledge, developers interested in secure systems design, and business professionals who need to understand cybersecurity risks and controls. Whether you're transitioning into cybersecurity or strengthening your existing technical foundation, this course provides essential knowledge for protecting digital assets and information systems.
Data Management for Analytics Part 2
Northeastern University (via Coursera)
This course will offer you an opportunity to learn the fundamental concepts and emerging technologies in data storage and data governance. It presents a balanced theory-practice focus and covers Structured Query Language, and two flavors of NoSQL databases in MongoDB and Neo4j graph database. It also includes a brief introduction to big data management including hadoop, MapReduce, and Apache Spark. By the end of this part 2 course on data analytics, you will have a foundational understanding of the theory and applications of database management to support data analytics, data mining, machine learning, and artificial intelligence.
User Experience Design and Testing Part 2
Northeastern University (via Coursera)
This course will offer you an opportunity to learn about additional design planes, design thinking, and prototyping techniques. The concepts in this course will prepare you to work with modern design software, apply design techniques, and how to use common design software. Throughout your time in this course, you will be given opportunities to check your understanding of course material, as well as engage in quizzes to reflect on all the concepts you have explored within each module. By the end of this part 2 course on user experience and design testing, you will have a foundational understanding of the design planes and user testing.
Practical AI for Professionals
Northeastern University (via Coursera)
Explore key ideas in Artificial Intelligence (AI) while delving into trending developments in the field. Examines AI tools and frameworks to enable collaboration effectively and efficiently across technical and non-technical stakeholders. Analyze topics such as AI-enabled perception, representation, reasoning, and learning as contextualized by societal impact. Equips students with the knowledge and skills necessary to confidently navigate the ever-evolving landscape of artificial intelligence
Evaluating the Quality of Healthcare Delivery
Northeastern University (via Coursera)
In this course, you will have the opportunity to learn about the great progress that has been made in measuring and evaluating quality of care. We will discuss key concepts and methods. You will also learn about how to use websites for comparing the quality of healthcare providers. The course content is intended for a wide range of participants – for example, people who have a general interest in quality of care, consumers seeking information about how to choose a provider for themselves or family members, or leaders of business organizations who are responsible for employee health insurance benefits and network of providers. By the end of this course, the learner should be able to: 1. Explain key developments regarding how quality of care is measured and evaluated in the US. 2. Articulate basic framework for evaluating quality of outcomes of care including types of and criteria for selecting quality measures for evaluating and comparing providers. 3. Discuss scientific issues and challenges for evaluating quality of care and methods for addressing these challenges. 4. Identify and apply resources and tools for comparing the quality of care of providers.
Enterprise Data Wrangling with SQL and Python
Northeastern University (via Coursera)
Welcome to Enterprise Data Wrangling with SQL and Python. This course will cover data wrangling principles and techniques for business. Key topics include data extraction, profiling, cleansing, integration, transformation, and automating data processes for business purposes. In the course, you will apply principles and techniques using data transformation tools, programming languages, and data process automation tools. The course offers you an opportunity to learn how to embed appropriate communication mechanisms for collaboration to identify and resolve real-world data challenges revealed in datasets and business processes, creating business value in today’s disparate computing and dynamic business environment.
Statistical Learning for Engineering Part 1
Northeastern University (via Coursera)
This course covers practical algorithms and the theory for machine learning from a variety of perspectives. Topics include supervised learning (generative, discriminative learning, parametric, non-parametric learning, deep neural networks, support vector Machines), unsupervised learning (clustering, dimensionality reduction, kernel methods). The course will also discuss recent applications of machine learning, such as computer vision, data mining, natural language processing, speech recognition and robotics. Students will learn the implementation of selected machine learning algorithms via python and PyTorch.
UX Web Design: Build User-Centric Websites
Northeastern University (via Coursera)
Welcome to UX Web Design: Build User-Centric Websites. Jumpstart your journey in UX design with this course, blending theory and practice to teach you the essentials. Learn key UX principles, align products with user needs, and dive into user research to craft intuitive and engaging digital experiences. Gain hands-on experience in creating wireframes and prototypes, using tools like Balsamiq to bring your designs to life. This course sets the foundation for anyone looking to create user-centered websites and apps, providing the skills needed to innovate and meet user expectations effectively.
Economic Decision Making Part 2
Northeastern University (via Coursera)
Explores economic modeling and analysis techniques for selecting alternatives from potential solutions to an engineering problem. Considers measures of merit, such as present worth, annual worth, rate of return, and benefit/cost techniques. Examines recent techniques of economic analysis, especially the tools of decision-making. Explores decisions under uncertainty. Studies the causes of risk and uncertainty and examines ways to change and influence the degree of risk and uncertainty through sensitivity analysis, expectation-variance criterion, decision tree analysis, statistical decision techniques, and multiple attribute decision-making through group case studies.
Engineering Probability and Statistics Part 1
Northeastern University (via Coursera)
Welcome to Engineering Probability and Statistics Part 1. Throughout your time in this course, you will be given opportunities to check your understanding of course material, as well as engage in quizzes to reflect on all the concepts you have explored within each module. By the end of this part 1 course on engineering probability and statistics, you will have a foundational understanding of the fundamentals of statistics, probability, variables, and types of distributions.
Mastering UX & Business App Development with OOP
Northeastern University (via Coursera)
This course is an introduction to the Java programming language and the concepts of object-oriented design. It not only covers the fundamentals of programming in Java, but it also brings in the concepts of object-oriented design and guides students to build GUI-based applications to address real-world problems. Topics include, but not limited to, fundamentals of programming in Java, classes and methods, objects and references, overloading, inheritance, polymorphism, abstract classes and interfaces, basic data structures, and GUI applications. Students are expected to apply learned knowledge to address an identified problem found in the real world.
Effective Talent Management & Development
Northeastern University (via Coursera)
Offers students an opportunity to obtain the insights, frameworks, and tools to effectively manage and develop talent in teams and organizations. Also explores promotion and cross-functional systems that strengthen the organization as well as retention strategies to promote and reward high-quality talent. Managing and developing talent is one of the top three issues on the minds of CEOs from around the world. In fact, CEOs cite managing and developing their leadership talent as the issue that is most important to the future success of their business but that their organizations are least capable of addressing effectively. Offers students an opportunity to engage in various activities intended to illustrate and practice the skills involved in implementing talent management systems.
Machine Learning and Data Analytics Part 2
Northeastern University (via Coursera)
This course delves into both the theoretical aspects and practical applications of data mining within the field of engineering. It provides a comprehensive review of the essential fundamentals and central concepts underpinning data mining. Additionally, it introduces pivotal data mining methodologies and offers a guide to executing these techniques through various algorithms. Students will be introduced to a range of data mining techniques, such as clustering, the extraction of association rules, support vector machines, neural networks, and the exploration of other complex techniques. Additionally, we will use case studies to explore the application of data mining across diverse sectors, including but not limited to manufacturing, healthcare, medicine, business, and various service industries.
Strategic Info Systems: Planning & Business Alignment
Northeastern University (via Coursera)
This course introduces key project management principles for IT systems development. You'll learn about project planning, scope management, Agile methodologies, and creating project charters and management plans. Emphasis is placed on aligning projects with business goals and managing requirements to ensure successful outcomes
Foundations in Human-Centered AI
Northeastern University (via Coursera)
In this course, we will explore the foundations of Human-Centered AI, a subdomain of artificial intelligence research that asks the core question underlying our study: How do we design AI technology in ways to augment and enhance human capability, rather than replace it outright? We will begin by examining the history of research and technology around artificial intelligence, situating our current understanding of AI in a broader historical lens that will supply some of the motivations around why it matters to design AI with a human-centric orientation. From there, we will consider some of the key concepts, tenets, and challenges of Human-Centered AI.
Application Engineering and Development Part 1
Northeastern University (via Coursera)
This course is an introduction to the Java programming language and the concepts of object-oriented design. It not only covers the fundamentals of programming in Java, but it also brings in the concepts of object-oriented design. Topics include, but are not limited to, fundamentals of programming in Java, classes and methods, objects and references, overloading, inheritance, polymorphism, abstract classes and interfaces, basic data structures, and GUI applications. Students are expected to apply learned knowledge to address an identified problem found in the real world.
Machine Learning in Healthcare: Fundamentals & Applications
Northeastern University (via Coursera)
Examines data mining perspectives and methods in a healthcare context. Introduces the theoretical foundations for major data mining methods and studies how to select and use the appropriate data mining method and the major advantages for each. Students are exposed to contemporary data mining software applications and basic programming skills. Focuses on solving real-world problems, which require data cleaning, data transformation, and data modeling.
Introduction to Software Development and Applications
Northeastern University (via Coursera)
The primary objectives of this course are to introduce software engineering techniques and their application to real-world business problems. You will be equipped with practical design and programming techniques for the purpose of modeling significant business applications quickly. In a step-by-step manner, the instructor will take you through the process of systematically combining object-oriented programming techniques, business processes, and complex data models to assemble models that are user friendly and meet business requirements. You will learn how to employ systems thinking, the object-oriented paradigm, the visual programming technique, as well as productivity tools to put together complicated, powerful designs. We will practice simple and smart ways of making software programming enjoyable.
Machine Learning with Small Data Part 1
Northeastern University (via Coursera)
This course addresses the challenge of machine learning (ML) in the context of small datasets, a significant issue due to ML's increasing data demands. Despite ML's success in various fields, many areas can't provide large labeled datasets because of costs, privacy, or security laws. As big data becomes standard, efficiently learning from smaller datasets is crucial. This course, ideal for graduate students with some ML experience, focuses on modern deep learning techniques for small data applications relevant in healthcare, military, and various industry sectors. Prerequisites include ML familiarity and Python proficiency. Deep learning experience is not necessary but beneficial.
Mastering Negotiation Skills & Strategies
Northeastern University (via Coursera)
Designed to improve students’ understanding of the negotiations process and their ability to plan and conduct negotiations effectively. Includes such activities as readings, lectures, and discussions as well as case discussions and role-playing negotiation exercises.
Generative AI: Foundations and Concepts
Northeastern University (via Coursera)
This course provides an overview of some different concepts underpinning Generative AI, their mathematical principles, and their applications in engineering. The focus will be on the practical implementation of generative AI including, neural networks, attention mechanism, and advanced deep learning models.
Data Management and Database Design Part 2
Northeastern University (via Coursera)
Data Management and Database Design Part 2 advances your database expertise with performance optimization, advanced SQL, enterprise administration, and cloud technologies. Complete your project database while mastering production-level skills in security, scaling, and distributed systems. Build the advanced competencies needed for senior database and data architect roles.
Healthcare Analytics Essentials
Northeastern University (via Coursera)
This course is best suited for individuals currently in the healthcare sector, as a provider, payer, or administrator. Individuals pursuing a career change to the healthcare sector may also be interested in this course. In this course, you will have an opportunity to examine topics related to data-driven decision making in healthcare. You will be asked to consider both the patient and provider perspective and their contributions to improving the quality of care provided. Through the readings, the application of the analytical tools, and the concepts and principles in this course, you will have a more comprehensive understanding of the complexity of healthcare delivery organizations and how they affect patient care delivery and ultimately patient medical outcomes. This course provides you the opportunity to: ~ Describe how healthcare business analytics fits into the data science and business disciplines ~ Identify key current issues in analytics and data science ~ Describe how business analytics integrates with business strategy
Promoting Equal Opportunity & Diversity in Workplaces
Northeastern University (via Coursera)
Examines issues including discrimination and bias, sexual harassment and workplace romance, professional and personal development, power and privilege, work and family, and organizational strategies for promoting equal opportunity and a multicultural approach for leveraging diversity and inclusion. Diversity in the workplace involves recognizing and capitalizing on individual differences such as religion, gender, race, ethnicity, sexual orientation, national origin, age, and physical ability/disability. Leaders need to address issues of diversity in strategic and ethical ways if they are to compete and succeed in a global economy.
Understanding the U.S. Healthcare Landscape
Northeastern University (via Coursera)
This course is best suited for individuals currently in the healthcare sector, as a provider, payer, or administrator. Individuals pursuing a career change to the healthcare sector may also be interested in this course. This course is the continuation of An Overview of the U.S. Healthcare System course . If you have not yet taken the introductory course, it is recommend that you complete that course prior to this course. The foundational knowledge from the introduction is carried through in this deeper dive into learning about how the U.S. Healthcare System operates. This course provides an insight into the payment architecture, cost and value of prescription drugs, spending, outcomes, and social accountability of the American Healthcare System. Throughout this course, you will be given the opportunity to evaluate your understanding through engagement in course discussions, application of course concepts to course assignments, and through completion of content quizzes along the way.
Introduction to Enterprise Growth and Innovation
Northeastern University (via Coursera)
This course is best suited for individuals currently in the healthcare sector, as a provider, payer, or administrator. Individuals pursuing a career change to the healthcare sector may also be interested in this course. The course explores the challenges and processes for harnessing technological innovation for new-business development, with special focus on digital healthcare transformation. You will gain an understanding of enterprise growth and innovation topics through readings, cases, and exercises, including learning how firms from different industries gain competitive advantage through distinctive products and services. The vast expertise of faculty combined with topic perspectives from the Mayo Clinic make this an engaging and unique course.
Intro to Strategic Management for Healthcare Organizations
Northeastern University (via Coursera)
This course is best suited for individuals currently in the healthcare sector, as a provider, payer, or administrator. Individuals pursuing a career change to the healthcare sector may also be interested in this course. In this course, you will have an opportunity to explore general business strategy concepts as they relate to the healthcare industry. You will also examine how strategic decisions are made within organizations. After an introduction to the different levels of strategy, through examples, you will look at each level in greater detail. You will also have the opportunity to conduct an external evaluation that explores market, environment, customer, and competitor analyses.
Machine Learning with Small Data Part 2
Northeastern University (via Coursera)
By completing this course, you'll master building powerful machine learning systems that excel with limited data. You'll gain expertise in multi-task learning, meta-learning, and advanced data augmentation—from physics-based simulations to generative approaches—enabling models to adapt quickly and perform beyond their dataset size. What makes this course unique is its focus on cutting-edge 3D and generative technologies: Neural Radiance Fields (NeRF), diffusion models, and 3D Gaussian Splatting. Unlike traditional ML courses that assume abundant data, this program tackles real-world constraints while unlocking advanced capabilities in science, engineering, and creative industries. This course is primarily aimed at graduate students in computer science, engineering, or data science, along with industry professionals and researchers working with limited datasets who need to develop high-performance machine learning systems despite data constraints.
Planning and Managing Information Systems Development Part 1
Northeastern University (via Coursera)
This course provides an overview of the most popular information systems needs’ assessment methodologies including portfolio analysis, stage assessment, business systems planning. Topics include utilities Information Systems strategic plan prioritization techniques of business goal alignment, architectural compatibility, and cost/benefit and risk analysis to demonstrate how businesses match needs to budgetary constraints. Describes and evaluates options for the placement of the Information Systems function within the organization and a variety of methods to manage the function.
Strategic Healthcare Workforce Management
Northeastern University (via Coursera)
Introduces how to measure and manage a workforce strategically, including (1) identifying the strategic work that is truly necessary to execute firm strategy; (2) investing in differentiated management systems that support that work; and (3) designing and implementing targeted measurement systems, such as human resources function and workforce scorecards, designed to help to hold line managers accountable for strategic talent. Emphasizes helping students move from a focus on levels associated with a particular workforce attribute (e.g., what is our cost per hire?) to understanding the impact of the workforce on business-level outcomes (e.g., how might an increase in the quality of our project managers affect new product cycle time?).
An Overview of the U.S. Healthcare System
Northeastern University (via Coursera)
This is the first part of a two part course on the U.S Healthcare System. This course will offer you an opportunity to examine concepts and topics related to understanding how the healthcare ecosystem works in the United States. During this course, you will have an opportunity to explore concepts and topics related to funding, payment, service delivery, and outcome structures of the American healthcare system. You will be given the opportunity to study the opportunities and challenges presented in improving the cost, quality, and accessibility of healthcare and expanding adequate coverage to all. Throughout this course, you will be asked to look at healthcare through a global lens, comparing different healthcare models for countries world wide and to consider the complexities and challenges countries face when creating healthcare delivery models. You will demonstrate an understanding of the American healthcare system through completing a series of assignments that encourage you to reflect on course concepts, your personal experiences, current events, and discussions with your colleagues in this course.
Application Engineering and Development Part 2
Northeastern University (via Coursera)
This course is an introduction to the Java programming language and the concepts of object-oriented design. It not only covers the fundamentals of programming in Java, but it also brings in the concepts of object-oriented design. Topics include, but are not limited to, fundamentals of programming in Java, classes and methods, objects and references, overloading, inheritance, polymorphism, abstract classes and interfaces, basic data structures, and GUI applications. Students are expected to apply learned knowledge to address an identified problem found in the real world.
Engaging in Enterprise Growth and Innovation
Northeastern University (via Coursera)
This course is the continuation of "Introduction to Enterprise Growth and Innovation". If you have not visited the first part yet, please check it out before starting this course. If you have finished the first part of this series: Introduction to Enterprise Growth and Innovation, you will be able to apply what you learned to your own career. You will explore the challenges and processes for harnessing technological innovation for new-business development, with special focus on digital healthcare transformation. You will gain an understanding of enterprise growth and innovation topics through readings, cases, and exercises, including learning how firms from different industries gain competitive advantage through distinctive products and services. The vast expertise of faculty combined with topic perspectives from the Mayo Clinic make this an engaging and unique course. It's important to note that if you like what your learning in this course and have a healthcare innovation project that you want to see if you can fully realize, consider enrolling in the for-credit version of this course, part of the MS in Management: Digital Transformation in Healthcare degree.
Introduction to Machine Learning and Algorithmic Bias
Northeastern University (via Coursera)
This course explores the intersection of artificial intelligence (AI), machine learning (ML), and responsible business practice in our increasingly AI-driven economy. Participants establish foundational understanding of AI and ML concepts, their real-world applications, and factors driving their widespread adoption across industries. The course presents the machine learning process—from data collection and preparation through model development and evaluation—providing practical insights into how data transforms into actionable business insights. Significant attention is dedicated to algorithmic bias, a critical challenge that can undermine system effectiveness and create unintended disparities in AI applications. Through examination of real-world cases across sectors such as recruitment, healthcare, and financial services, participants learn to identify different types of bias—historical bias, representation bias, and measurement bias—and understand their business implications. The course concludes with practical strategies for bias detection and mitigation, along with governance frameworks for AI deployment. Participants gain the knowledge needed to build AI systems that work effectively for diverse populations while delivering reliable business value, preparing future leaders to harness AI's transformative potential while managing its risks and ensuring broad accessibility. This course is best suited for individuals seeking to advance their careers through skill-building, industry application, and network expansion. Whether aiming for a promotion, transitioning to a new career, or growing one’s professional skills, learners will gain valuable insights into how they can contribute to their organizations and articulate those ideas with peers, recruiters, and other stakeholders.
Business Strategy and Value Creation In Action
Northeastern University (via Coursera)
In the world of business and organizations, nothing is more important than having an effective strategy. Why? Because without knowing our destination, we cannot determine the right path to get there. This course introduces the two sides of a strategy: competitive strategy and corporate strategy. Competitive strategy has to do with the environment in which firms and organizations are operating and how they can develop and sustain their competitive advantage. On the other hand, corporate strategy has to do with the specific strategies firms undertake to sustain their competitive advantage, such as product diversification, internationalization, and non-market strategies. This course is best suited for individuals seeking to advance their careers through skill-building, industry application, and network expansion. Whether aiming for a promotion, transitioning to a new career, or growing one’s professional skills, learners will gain valuable insights into how they can contribute to their organizations and articulate those ideas with peers, recruiters, and other stakeholders.
Web Design and User Experience Engineering: Assessment
Northeastern University (via Coursera)
In this course you will have the opportunity to complete a comprehensive proctored assessment in order to demonstrate your knowledge of the subject matter. This module contains information on the proctoring process, your comprehensive assessment, how to submit the Certificates of Completion you’ve obtained from Part 1 and Part 2 of this course, and instructions on how to enroll with Northeastern University through Performance Based Admission (PBA).
Intro to Managing Healthcare Supply Chain Operations
Northeastern University (via Coursera)
This course is best suited for individuals currently in the healthcare sector, as a provider, payer, or administrator. Individuals pursuing a career change to the healthcare sector may also be interested in this course. In this course, you will have an opportunity to explore concepts and topics related to the design and management of operations and supply chains in the healthcare sector. After an introduction to operations and supply chain management, you will examine the different dimensions and principles of quality and reflect on approaches to operational process improvement. Throughout this course, you will be given the opportunity to apply the course concepts to an operational process improvement project.
Machine Learning and Data Analytics Part 1
Northeastern University (via Coursera)
This course delves into both the theoretical aspects and practical applications of data mining within the field of engineering. It provides a comprehensive review of the essential fundamentals and central concepts underpinning data mining. Additionally, it introduces pivotal data mining methodologies and offers a guide to executing these techniques through various algorithms. Students will be introduced to a range of data mining techniques, such as data preprocessing, the extraction of association rules, classification, prediction, clustering, and the exploration of complex data, and will implement a capstone project exploring the same. Additionally, we will use case studies to explore the application of data mining across diverse sectors, including but not limited to manufacturing, healthcare, medicine, business, and various service industries.
Intro to Finance in Healthcare
Northeastern University (via Coursera)
This course is best suited for individuals currently in the healthcare sector, as a provider, payer, or administrator. Individuals pursuing a career change to the healthcare sector may also be interested in this course. In this course, you will have an opportunity to explore concepts and topics related to accounting and finance basics for healthcare organizations. After an introduction to the financial statements of healthcare entities, you will then learn how to read, interpret, and use a financial statement in order to understand the financial health of an organization. Your attention will be primarily focused on the Balance Sheet and Income Statement and basics surrounding revenue and expenses. This course will tie together the financial elements learned, to the risks facing healthcare entities, as the industry continues to evolve from the COVID 19 pandemic and its resulting impact on labor, supply chain expenses, and value-based care reimbursement models. Throughout this course, you will be given the opportunity to evaluate your understanding through engagement in course discussions, application of course concepts to a course assignment, and through completion of content quizzes along the way.
Responsible AI for Mental Health
Northeastern University (via Coursera)
Unlock the future of AI-driven mental health care while tackling the critical ethical challenges shaping the field today. From bias and misinformation to privacy and patient safety, this course dives into the complexities of AI’s role in mental health. Explore cutting-edge advancements in computing and social robotics, and compare basic and advanced NLP techniques used in mental health analysis. Gain insight into emerging trends that are transforming therapy, diagnostics, and patient support, and examine how AI can be both a powerful tool and a potential risk in mental healthcare. Designed for mental health professionals, policymakers, and tech leaders, this course empowers you to shape responsible AI frameworks that prioritize fairness, transparency, and safety. Whether you're looking to influence policy, integrate AI into healthcare, or understand the future of mental health technology, this course provides the expertise to make an impact. Join us and be at the forefront of building ethical, effective, and human-centered AI for mental health.
Systems and Cybersecurity Fundamentals Part 2
Northeastern University (via Coursera)
This course is best suited for individuals who have completed Part 1 or possess equivalent foundational cybersecurity knowledge and wish to advance their skills in network security, identity management, threat detection, and secure development practices. This course is ideal for security analysts, network administrators, identity and access management professionals, incident responders, and developers implementing DevSecOps practices. If you're looking to move beyond security fundamentals into implementing comprehensive security architectures and responding to real-world threats, this course will provide the advanced knowledge and practical skills you need.
Industrial Optimization: Models & Linear Programming
Northeastern University (via Coursera)
Introduces the theory, computation, and application of deterministic models to represent industrial operations. Includes linear programming formulation and solution using spreadsheet and algebraic languages software; simplex, big-M, revised simplex, and dual simplex algorithms for solving linear programs; introduction to the theory of simplex.
Web Design and User Experience Engineering Part 1
Northeastern University (via Coursera)
Introduces the fundamentals of developing web user-interface/user-experience (UI/UX). This course will focus on core concepts and best practices involved in developing web applications that are not tied to specific libraries or frameworks. Topics include HTML, CSS, Javascript, and basic accessibility (a11y).
Engaging in Service Innovation and Management
Northeastern University (via Coursera)
This course is the continuation of "Introduction to Service Innovation and Management". If you have not yet taken "Introduction to Service Innovation and Management", it is recommended that you complete that course prior to this course. The foundational knowledge and project plan from the introduction are carried through in this deeper dive into service innovation and management. This course will give you tools to examine initial plans for healthcare service/process redesign. You will be exposed to important topics such as defining and evaluating processes, planning for organizational change, team management, the role of culture in maintaining and supporting new processes, the management of stakeholders, both internal and external, and the role of leadership at all levels of the organization. You will learn about best practices in examining strategies based on different organizational models, continuous process improvements, resistance, employee empowerment, and the role of leadership in managing operations. Through the project work you will have the opportunity to apply these concepts to services and internal business processes at your own organizations.
Agile Business Processes: Systems for Operational Success
Northeastern University (via Coursera)
The primary objectives of this course are to introduce business process concepts and strategies. You will learn how to understand and specify the flow of work responsibility and movement of information throughout an enterprise. For businesses to maximize the benefits of technology, they must transform their ad-hoc and often poorly defined ways of doing things to formal business processes. In addition, you will explore frameworks for business process management. You will also learn about the importance of business mapping as well as how to analyze stakeholders and keep them involved in the process.
Program Structure and Algorithms Part 2
Northeastern University (via Coursera)
This course will guide you through the essential principles of algorithms and their significance in computational problem-solving. You'll begin by exploring what an algorithm is, its core characteristics, and how it applies to real-world scenarios—from simple everyday tasks to complex computing challenges. As you progress, you will learn about the critical role algorithms play in improving efficiency and scalability across various fields. We’ll break down key concepts such as algorithmic complexity, helping you evaluate the efficiency of different approaches, which will ultimately guide your decision-making.
Software Quality Control and Management Part 1
Northeastern University (via Coursera)
Welcome to Software Quality Control and Management: Get ready to explore how quality assurance brings software to life! In this course, you’ll learn what Software Quality Assurance (SQA) is, why it matters, and how it fits into the Software Development Life Cycle (SDLC). You’ll see where development and QA teams collaborate to deliver reliable, high-performing products. You’ll dive into QA methodologies like Waterfall, Agile, and DevOps, discovering how testing adapts to each approach. You’ll also learn about the different phases and types of QA testing, from manual checks to full automation. Hands-on practice is a big part of this course—you’ll use two of the most common automation tools in the industry, UFT (Unified Functional Testing) and Selenium, to build your testing skills. By the end, you’ll also explore career opportunities in IT and QA, helping you understand how your new skills can open doors in the tech world.
Statistical Learning for Engineering Part 2
Northeastern University (via Coursera)
This course covers practical algorithms and the theory for machine learning from a variety of perspectives. Topics include supervised learning (generative, discriminative learning, parametric, non-parametric learning, deep neural networks, support vector Machines), unsupervised learning (clustering, dimensionality reduction, kernel methods). The course will also discuss recent applications of machine learning, such as computer vision, data mining, natural language processing, speech recognition and robotics. Students will learn the implementation of selected machine learning algorithms via python and PyTorch.
Software Quality Control and Management Part 2
Northeastern University (via Coursera)
Welcome to Software Quality Control and Management: Get ready to explore how quality assurance brings software to life! In this course, you’ll learn what Software Quality Assurance (SQA) is, why it matters, and how it fits into the Software Development Life Cycle (SDLC). You’ll see where development and QA teams collaborate to deliver reliable, high-performing products. You’ll dive into QA methodologies like Waterfall, Agile, and DevOps, discovering how testing adapts to each approach. You’ll also learn about the different phases and types of QA testing, from manual checks to full automation. Hands-on practice is a big part of this course—you’ll use two of the most common automation tools in the industry, UFT (Unified Functional Testing) and Selenium, to build your testing skills. By the end, you’ll also explore career opportunities in IT and QA, helping you understand how your new skills can open doors in the tech world.
Introduction to Service Innovation and Management
Northeastern University (via Coursera)
This course is best suited for individuals currently in the healthcare sector, as a provider, payer, or administrator. Individuals pursuing a career change to the healthcare sector may also be interested in this course. In this course, you will learn about the importance of successful execution and management of service innovation. The course focuses on the internal management of business processes necessary to deliver improved services to customers and patients, increased profitability, and build long-term customer loyalty and engagement. You will experience elements that are critical for the effective execution, implementation, and evaluation of the various strategic aspects of achieving organizational goals, with an emphasis on the initiatives and key organizational change elements. Through guided project work, you will have an opportunity to apply these concepts to services and internal business processes at your own organizations. Additionally, the course has been designed to help you become familiar with a framework of service and process redesign.
Innovation for Impact (i4i) The Carlson-Polizzotto Method of Value Creation
Northeastern University (via Coursera)
Welcome! Partnering with Tech industry giants Curtis Carlson and Len Polizzotto, Northeastern University brings you “Value Creation: The Carlson-Polizzotto Method” a short-form course experience like no other. Building careers by solving for the value proposition - Curt and Len are responsible for driving the integration of the software technology behind Apple’s voice command intelligent assistant and creating the standard for high definition television - now known to billions today as Siri and HDTV. So why do more than 50 percent of businesses fail? It’s because they are not identifying what their customers value. Watch Curt and Len coach 4 groups of professionals, each from distinctly different industries, tech, startup, education, and marketing, and learn alongside them as they use the Value Creation methodology to increase the power of their organization’s value proposition. Evaluate the benefits of implementing a Value Creation practice that can impact your own strategic business initiatives so you can successfully create your business’ value proposition.
Introduction to Domain Models
Northeastern University (via Coursera)
This course is a continuation of the Introduction to Software Development and Applications course. In this course, you will dive further into exploring software engineering techniques and their application to real-world business problems. Students who take this course will be equipped with practical design and programming techniques for the purpose of modeling significant business applications quickly. In this course you will learn about constructing domain models. You will also refine your skills to employ systems thinking, the object-oriented paradigm, the visual programming technique, as well as productivity tools to put together complicated, powerful designs. We will practice simple and smart ways of making software programming enjoyable.
NLP in Engineering: Concepts & Real-World Applications
Northeastern University (via Coursera)
This course provides an overview of some different Natural Language Processing (NLP) techniques, their underlying principles, and their applications in engineering. The focus will be on the practical implementation of NLP methods such as word embeddings, neural networks, attention mechanisms, and advanced deep learning models to solve real-world engineering problems.
Engaging in Improving Patient Experience Through Analytics
Northeastern University (via Coursera)
This course is best suited for individuals currently in the healthcare sector, as a provider, payer, or administrator. Individuals pursuing a career change to the healthcare sector may also be interested in this course. This is the second part in a two-part course exploring concepts and topics related to improving the patient experience and reducing pain points in healthcare processes through analytic and decision support frameworks. In this course, you will survey the kind of data that is used to make effective decision support choices, following up with information on how to use the data to predict outcomes. Throughout this course, you will be given the opportunity to apply the course concepts to operational improvements in your own organization.
Database to AI: Practical Data Analytics Integration
Northeastern University (via Coursera)
This course introduces the fundamental concepts and emerging technologies in database design and modeling, database systems, data storage, and data governance. It presents a balanced theory-practice focus and covers entity relationship model and UML model, relational model, relational databases, Structured Query Language, and two flavors of NoSQL databases in MongoDB and Neo4j graph database. It also includes a brief introduction to big data management including hadoop, MapReduce, and Apache Spark. This course provides the theory and applications of database management to support data analytics, data mining, machine learning, and artificial intelligence.
Planning and Managing Information Systems Dev: Assessment
Northeastern University (via Coursera)
In this course you will have the opportunity to complete a comprehensive proctored assessment in order to demonstrate your knowledge of the subject matter. This module contains information on the proctoring process, your comprehensive assessment, how to submit the Certificates of Completion you’ve obtained from Part 1 and Part 2 of this course, and instructions on how to enroll with Northeastern University through Performance Based Admission (PBA).
Computation and Visualization for Analytics Part 1
Northeastern University (via Coursera)
Offers students an opportunity to learn how to use visualization tools and techniques for data exploration, knowledge discovery, data storytelling, and decision making in engineering, healthcare operations, manufacturing, and related applications. Covers basics of Python and R for data mining and visualization. Introduces students to static and interactive visualization charts and techniques that reveal information, patterns, interactions, and comparisons by focusing on details such as color encoding, shape selection, spatial layout, and annotation.
Practical Engineering Data Mining: Techniques and Uses
Northeastern University (via Coursera)
This course delves into both the theoretical aspects and practical applications of data mining within the field of engineering. It provides a comprehensive review of the essential fundamentals and central concepts underpinning data mining. Additionally, it introduces pivotal data mining methodologies and offers a guide to executing these techniques through various algorithms. Students will be introduced to a range of data mining techniques, such as data preprocessing, the extraction of association rules, classification, prediction, clustering, and the exploration of complex data, and will implement a capstone project exploring the same. Additionally, we will use case studies to explore the application of data mining across diverse sectors, including but not limited to manufacturing, healthcare, medicine, business, and various service industries.
Aligning Business Strategy for AI Integration
Northeastern University (via Coursera)
Explores how artificial intelligence (AI) empowers businesses to enhance competitiveness. Examines how AI integrates with business strategy. Offers students an opportunity to recommend business solutions through the integration of AI capabilities. Focuses on leveraging machine learning techniques like unsupervised, supervised, and reinforcement learning for data-driven insights. Examines the intersection of managerial practices and AI capabilities through real-world case studies. Students also have an opportunity to gain practical insights into implementation and ethical considerations and navigate the dynamic landscape of AI-driven business transformations.
Healthcare Data Management and Information Systems
Northeastern University (via Coursera)
This course is the continuation of the Health Informatics for Healthcare Professionals course. If you have not yet taken the introductory course, it is recommend that you complete that course prior to this course. The foundational knowledge from the introduction is carried through in this deeper dive into informatics in healthcare. In this course, you will have an opportunity to explore concepts and topics related to the design and management of health information systems. This course covers cybersecurity, privacy, risk mitigation, data blocking, and the role of health information exchanges. It provides an overview of IT budgeting best practices. It also distinguish between pipeline and platform thinking in healthcare information technology and describes healthcare systems’ approaches to creating digital solutions for the future. Throughout this course, you will be given the opportunity to evaluate your understanding through engagement in course discussions, application of course concepts to course assignments, and through completion of content quizzes along the way.
Comprehensive UX and Responsive Web Design
Northeastern University (via Coursera)
This course covers the fundamentals of web UI/UX development, focusing on core concepts like HTML, CSS, JavaScript, and accessibility. You'll learn the history of web development, explore the HTTP protocol, and understand the interaction between servers and browsers. The course also introduces key tools like the command line and modern web development practices. In the final section, you'll be introduced to React, a popular JavaScript library, to apply your skills in building dynamic, interactive web pages. Throughout the course, you will be given the opportunity to test your knowledge through quizzes and apply them through a final peer review project: My Favorite Cats. Designed for beginners and those looking to strengthen their web development knowledge, this course equips you to create responsive, accessible websites.
Machine Learning for Healthcare Professionals
Northeastern University (via Coursera)
Examines data mining perspectives and methods in a healthcare context. Introduces the theoretical foundations for major data mining methods and studies how to select and use the appropriate data mining method and the major advantages for each. Students are exposed to contemporary data mining software applications and basic programming skills. Focuses on solving real-world problems, which require data cleaning, data transformation, and data modeling.
Ethics and AI: A Philosophical Guide to Responsible Use
Northeastern University (via Coursera)
The primary objectives of this course are to introduce concepts around defining AI and problematizing it's regulation, doing both from a philosophical standpoint. In this course, you'll be introduced to basic philosophical methods and have the opportunity to practice with logical statements. This practice will help you as you critically evaluate arguments for validity and soundness while forming your own opinion on the ethics of AI and AI regulation.