University of Alberta
Public University • CA
Showing 44 courses from UAlberta
Fundamentals of Reinforcement Learning - University of Alberta
University of Alberta (via Coursera)
Fundamentals of Reinforcement Learning - University of Alberta is a comprehensive intermediate-level resource offered by University of Alberta, focused on building practical skills in data science and analytics. 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 data science and analytics, including Python, SQL, Pandas, NumPy, data visualization, statistics, and machine learning basics. 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: Understand the core concepts and theoretical foundations Apply your knowledge through hands-on exercises and small projects Build the practical skills employers actually screen for Develop the problem-solving approach used by working professionals Duration: Estimated duration: 20 hours of content, designed to be completed in 2-4 weeks at a comfortable pace. Basic familiarity with the subject area is recommended. You should have completed a beginner-level course or have equivalent self-taught knowledge. Comfort with using a computer and basic problem-solving skills will help. 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 data science and analytics Freelancers wanting to add new services to their portfolio Self-learners passionate about data science and analytics 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 Data Analyst, Business Analyst, Data Scientist, Analytics Engineer. Realistic salary bands in India (2025-2026), based on Naukri/AmbitionBox data: Freshers / 0-2 years: Rs 4-8 LPA Mid-level / 2-5 years: Rs 10-22 LPA Senior / 5+ years: Rs 25-50 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 TCS, Infosys, Flipkart, Amazon, Swiggy, Zomato, PhonePe. The data science industry in India is projected to grow at 27% CAGR through 2028. Companies across all sectors — from banking (HDFC, ICICI) to e-commerce (Flipkart, Amazon) to healthcare (Practo, PharmEasy) — are building data teams. India currently has a shortage of 200,000+ data professionals, making this one of the best fields to enter right now. Cities like Bangalore, Hyderabad, Pune, and Gurgaon have the highest concentration of data science jobs. University of Alberta 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.
Reinforcement Learning Specialization - University of Alberta
University of Alberta (via Coursera)
Reinforcement Learning Specialization - University of Alberta is a comprehensive advanced-level resource offered by University of Alberta, 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: Understand the core concepts and theoretical foundations Apply your knowledge through hands-on exercises and small projects Build the practical skills employers actually screen for Develop the problem-solving approach used by working professionals Duration: Estimated duration: 80 hours of content, designed to be completed in 8-16 weeks at a comfortable pace. This is an advanced resource meant for learners who already have solid fundamentals. You should have at least 6 months of hands-on experience or have completed intermediate-level courses in this area. 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: The course content is free to access. A verified certificate is available for a fee. 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. University of Alberta 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.
Sample-based Learning Methods - University of Alberta
University of Alberta (via Coursera)
Sample-based Learning Methods - University of Alberta is a comprehensive advanced-level resource offered by University of Alberta, 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: Understand the core concepts and theoretical foundations Apply your knowledge through hands-on exercises and small projects Build the practical skills employers actually screen for Develop the problem-solving approach used by working professionals Duration: Estimated duration: 15 hours of content, designed to be completed in 2-3 weeks at a comfortable pace. This is an advanced resource meant for learners who already have solid fundamentals. You should have at least 6 months of hands-on experience or have completed intermediate-level courses in this area. 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. University of Alberta 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.
Prediction and Control with Function Approximation - Alberta
University of Alberta (via Coursera)
Prediction and Control with Function Approximation - Alberta is a comprehensive advanced-level resource offered by University of Alberta, 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: Understand the core concepts and theoretical foundations Apply your knowledge through hands-on exercises and small projects Build the practical skills employers actually screen for Develop the problem-solving approach used by working professionals Duration: Estimated duration: 15 hours of content, designed to be completed in 2-3 weeks at a comfortable pace. This is an advanced resource meant for learners who already have solid fundamentals. You should have at least 6 months of hands-on experience or have completed intermediate-level courses in this area. 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. University of Alberta 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.
Software Processes and Agile Practices
University of Alberta (via Coursera)
This course delves into a variety of processes to structure software development. It also covers the foundations of core Agile practices, such as Extreme Programming and Scrum.
Becoming Your Best Self at Work
University of Alberta (via Coursera)
This course is designed to give you practical insights and tools that you can apply in both your personal and professional life. We’ll explore what happiness truly means, challenging common misconceptions and uncovering what actually contributes to lasting well-being. By understanding this, you can make more intentional choices that enhance your fulfillment at work and beyond. From there, we’ll take a closer look at how work impacts mental health, not just in moments of high stress, but in the everyday interactions and expectations that shape our well-being. We’ll dive into diversity, equity, and inclusion, focusing on how inclusive environments don’t just benefit some people—they create better workplaces for everyone.
How to be a People Leader
University of Alberta (via Coursera)
In this course, we’ll be looking at leadership through the lens of psychological health and safety, which means we’ll be diving into the real workplace factors that shape well-being—things like stress, burnout, inclusion, communication, and conflict resolution. We start by laying the foundation of strong leadership—what makes an effective leader, how your leadership style impacts your team, and how you can build trust, engagement, and accountability in your workplace. We’ll also focus on employee mental health—how to recognize when someone on your team may be struggling, how to support them effectively, and how to ensure that mental health conversations are handled in a way that reduces stigma and fosters trust.
Science & Religion 101
University of Alberta (via Coursera)
This course examines the nature of both science and religion and attempts to explore the possible relationships between them. The primary purpose is to dispel the popular myth that science and religion are entrenched in a never-ending conflict. As a result, this course argues that if the limits of both science and religion are respected, then their relationship can be complementary. Topics include: Science and Religion Categories and Foundational Principles, Definitions of Science and Religion, Science-Religion Models and Relationships, Intelligent Design and Natural Revelation, the Galileo Affair, Geology and Noah’s Flood, Evolution and Darwin’s Religious Beliefs, the Modern “Evolution” vs. “Creation” Debate, the Problem of Evil, and Interpretations of the Biblical Accounts of Origins in Genesis 1-11. The course employs a Constructive Teaching Style in order that students can develop their personal views on the relationship between science and religion and on each of the topics listed above. St. Joseph's College is a Catholic, undergraduate, liberal arts college on the University of Alberta campus. It is an independent institution that is affiliated with the University of Alberta. Denis O. Lamoureux is Professor of Science and Religion at St. Joseph's College in the University of Alberta. He is the author of Evolutionary Creation: A Christian Approach to Evolution (2008), Evolution: Scripture and Nature Say Yes! (2016), and The Bible & Ancient Science: Principles of Interpretation (2020). Lamoureux is a Research Associate in Paleontology and has contributed to a dozen scientific papers. He is cited in the Who’s Who of Theology and Science and has delivered over 600 lectures throughout the United States and Canada. Lamoureux holds three earned doctoral degrees—dentistry, theology, and biology.
Fighting Misinformation in Public Health
University of Alberta (via Coursera)
This introductory course examines the foundations of health misinformation and disinformation and how they affect public health. Learners explore the distinction between public and individual health, key drivers of misinformation, and common psychological influences such as confirmation bias and the illusory truth effect. The course introduces core concepts, red flags, and scientific literacy fundamentals, including peer review, retractions, and how vaccines work, to help learners build a strong public health literacy toolkit. This course is part of the "Fighting Misinformation in Public Health" certificate program offered by the University of Alberta Continuing Education. For more information, visit this page: https://coned.ualberta.ca/public/category/courseCategoryCertificateProfile.do?method=load&certificateId=22473053
Introdução ao Gerenciamento de produtos de software
University of Alberta (via Coursera)
Este curso destaca a importância e o papel do gerenciamento de produtos de software. Também fornece uma visão geral da especialização, bem como suas metas, estrutura e expectativas. O curso explica o valor do processo, requisitos, planejamento e monitoramento na produção de um software melhor.
Indigenous Canada
University of Alberta (via Coursera)
Indigenous Canada is a 12-module course from the Faculty of Native Studies (University of Alberta). Through interdisciplinary lenses, this course invites you to build foundational knowledge about Indigenous histories and gain a deeper understanding of contemporary realities at global, national, and local levels. You will develop practical skills to: · Critically analyze colonial and Indigenous histories · Interpret treaties, land claims, and legal frameworks · Understand Indigenous political movements and resurgence · Contextualize current events, policy debates, and social movements · Recognize Indigenous approaches to land, environment, and knowledge · Engage thoughtfully with Indigenous worldviews and contemporary life, art, and creative expression Indigenous Canada encourages thoughtful reflection on Indigenous resilience and the responsibilities of living in shared spaces today. By the end of the course, you will be able to apply your knowledge and skills to academic, professional, and civic contexts, fostering more informed, respectful, and responsible engagement with Indigenous peoples and communities. You will leave with a greater appreciation for present-day Canada and how Indigenous perspectives can inform more just and sustainable relationships.
Creating a Workplace People Want to Be
University of Alberta (via Coursera)
In this course, we’ll examine what defines effective leadership at the senior level, how leadership styles influence workplace culture, and how to foster trust, accountability, and engagement across the organization. We’ll take a good look at the business case for improving psychological health and safety and then look at the tools and strategies you can use to assess your organization and develop the strategies you need to enhance your overall workplace culture. We’ll also explore the structural and cultural factors that shape employee well-being. Psychological safety, DEI, and harassment prevention will be discussed—not just as policies, but as leadership priorities that impact retention, morale, and performance. Finally, we’ll explore stress, burnout, and workplace culture at the organizational level. You’ll learn how to identify what contributes to burnout—and how to adjust these factors to build a resilient, high-performing organization.
Object-Oriented Design
University of Alberta (via Coursera)
This course takes Java beginners to the next level by covering object-oriented analysis and design. You will discover how to create modular, flexible, and reusable software, by applying object-oriented design principles and guidelines. And, you will be able to communicate these designs in a visual notation known as Unified Modelling Language (UML). You will be challenged in the Capstone Project to apply your knowledge of object-oriented design by evolving and documenting the Java codebase for an Android application with corresponding UML documentation. After completing this course, you will be able to: • Apply the Class Responsibility Collaborator (CRC) technique to analyze and design the object-oriented model for a problem. • Explain and apply object-oriented modeling principles and their purpose (e.g., abstraction, encapsulation, decomposition, generalization). • Explain and apply different types of inheritance • Explain the difference between association, aggregation, and composition dependencies. • Express object-oriented models as Unified Modeling Language (UML) class diagrams. • Translate between UML class diagrams and equivalent Java code. • Apply design guidelines for modularity, separation of concerns, information hiding, and conceptual integrity to create a flexible, reusable, maintainable design. • Explain the tradeoff between cohesion and coupling.
Software Architecture
University of Alberta (via Coursera)
The way that software components — subroutines, classes, functions, etc. — are arranged, and the interactions between them, is called architecture. In this course you will study the ways these architectures are represented, both in UML and other visual tools. We will introduce the most common architectures, their qualities, and tradeoffs. We will talk about how architectures are evaluated, what makes a good architecture, and an architecture can be improved. We'll also talk about how the architecture touches on the process of software development. In the Capstone Project you will document a Java-based Android application with UML diagrams and analyze evaluate the application’s architecture using the Architecture Tradeoff Analysis Method (ATAM). After completing this course, you will be able to: • Compare and contrast the components, connections, protocols, topologies, constraints, tradeoffs, and variations of different types of architectural styles used in the design of applications and systems (e.g., main program and subroutine, object-oriented, interpreters, pipes and filters, database centric, event-based). • Describe the properties of layered and n-tier architectures. • Create UML ipackage, component, and deployment diagrams to express the architectural structure of a system. • Explain the behaviour of a system using UML activity diagrams. • Document a multi-application system with a layered architecture.
Astro 101: Black Holes
University of Alberta (via Coursera)
What is a black hole? Do they really exist? How do they form? How are they related to stars? What would happen if you fell into one? How do you see a black hole if they emit no light? What’s the difference between a black hole and a really dark star? Could a particle accelerator create a black hole? Can a black hole also be a worm hole or a time machine? In Astro 101: Black Holes, you will explore the concepts behind black holes. Using the theme of black holes, you will learn the basic ideas of astronomy, relativity, and quantum physics. After completing this course, you will be able to: • Describe the essential properties of black holes. • Explain recent black hole research using plain language and appropriate analogies. • Compare black holes in popular culture to modern physics to distinguish science fact from science fiction. • Describe the application of fundamental physical concepts including gravity, special and general relativity, and quantum mechanics to reported scientific observations. • Recognize different types of stars and distinguish which stars can potentially become black holes. • Differentiate types of black holes and classify each type as observed or theoretical. • Characterize formation theories associated with each type of black hole. • Identify different ways of detecting black holes, and appropriate technologies associated with each detection method. • Summarize the puzzles facing black hole researchers in modern science.
캡스톤 : 소프트웨어 제품 관리 실전 프로젝트
University of Alberta (via Coursera)
6주 간의 캡스톤 과정을 진행하는 동안 여러분은 안전한 가상 소프트웨어 제품 생산 환경에서 실질적인 관리 경험을 하게 됩니다. 애자일 방식과 기술을 적용해 현장에서 직면한 도전 과제를 극복하게 됩니다. 현실감 있는 고객과 소통하면서 고객의 니즈를 파악하고 실질적으로 필요한 소프트웨어 요구 사항을 전달해 생산을 촉진할 것입니다. 캡스톤 과정을 마치면 여러분은 당당한 소프트웨어 제품 관리 전문가로 성장할 것입니다.
Arctic Economy
University of Alberta (via Coursera)
Arctic communities have diverse histories and roles in local, regional and global economies. However, the scope and scale of globalization has increased so quickly that vulnerable Arctic communities are facing new kinds of challenges to their survival. In this 3-week MOOC, a unique collaboration between the University of Alberta and UiT The Arctic University of Norway, you will investigate the challenges faced by Indigenous, North American, Russian and Nordic Arctic communities in a modern world. So join us as we venture above the 60th parallel North, and explore how these fascinating communities adjust to change while maintaining their ways of life, socio-economic histories, and cultural traditions.
Client Needs and Software Requirements
University of Alberta (via Coursera)
This course covers practical techniques to elicit and express software requirements from client interactions.
Famine as Genocide: The Holodomor in Ukraine
University of Alberta (via Coursera)
The Holodomor, one of the major tragedies of the twentieth century, became the subject of serious study only since the fall of the USSR. In this course you will explore recent research through the prisms of colonialism, empire, genocide, famine and food security, (dis)information dissemination, and Ukrainian-Russian relations. Famine as Genocide in the 20th Century: The Case of the Holodomor makes the case that the Holodomor is crucial to understanding Ukrainian, Soviet, European, and world history, as well as current events. This course was developed by the Holodomor Research and Education Consortium, a project of the Canadian Institute of Ukrainian Studies at the University of Alberta, with the generous support of the Helen and Paul Baszucki Family and the Temerty Foundation.
Problem Solving, Python Programming, and Video Games
University of Alberta (via Coursera)
This course is an introduction to computer science and programming in Python. Upon successful completion of this course, you will be able to: 1. Take a new computational problem and solve it, using several problem solving techniques including abstraction and problem decomposition. 2. Follow a design creation process that includes: descriptions, test plans, and algorithms. 3. Code, test, and debug a program in Python, based on your design. Important computer science concepts such as problem solving (computational thinking), problem decomposition, algorithms, abstraction, and software quality are emphasized throughout. This course uses problem-based learning. The Python programming language and video games are used to demonstrate computer science concepts in a concrete and fun manner. The instructional videos present Python using a conceptual framework that can be used to understand any programming language. This framework is based on several general programming language concepts that you will learn during the course including: lexics, syntax, and semantics. Other approaches to programming may be quicker, but are more focused on a single programming language, or on a few of the simplest aspects of programming languages. The approach used in this course may take more time, but you will gain a deeper understanding of programming languages. After completing the course, in addition to learning Python programming, you will be able to apply the knowledge and skills you acquired to: non-game problems, other programming languages, and other computer science courses. You do not need any previous programming, Python, or video game experience. However, several basic skills are needed: computer use (e.g., mouse, keyboard, document editing), elementary mathematics, attention to detail (as with many technical subjects), and a “just give it a try” spirit will be keys to your success. Despite the use of video games for the main programming project, PVG is not about comput...
Emotional Vitality in a Dynamic Workplace
University of Alberta (via Coursera)
This course gives you easy access to knowledge and tools that will allow you to develop emotional intelligence in a work environment. Whether you work from home, or an office, you'll understand the importance of emotional vitality for building relationships and advancing your career. We will explore topics like emotional expedition, interpersonal dynamics, workplace stress, and recognition resonance to understand how to harness your emotions, enhance your relationships, and cultivate a positive and productive work environment.
Paleontology: Ancient Marine Reptiles
University of Alberta (via Coursera)
Paleontology: Ancient Marine Reptiles is a four-lesson course teaching a comprehensive overview of the evolutionary changes that occur when air-breathing terrestrial animals return to water. This course examines the diversity, adaptations, convergence, and phylogenetic relationships of extinct marine reptiles. Students will explore three major groups of marine reptiles: ichthyosaurs, plesiosaurs, and mosasaurs. Watch a preview of the course here: https://uofa.ualberta.ca/courses/paleontology-marine-reptiles
Agile Planning for Software Products
University of Alberta (via Coursera)
This course covers the techniques required to break down and map requirements into plans that will ultimately drive software production. Upon successful completion of this course, you will be able to: Create effective plans for software development Map user requirements to developer tasks Assess and plan for project risks Apply velocity-driven planning techniques Generate work estimates for software products
Reviews & Metrics for Software Improvements
University of Alberta (via Coursera)
This course covers techniques for monitoring your projects in order to align client needs, project plans, and software production. It focuses on metrics and reviews to track and improve project progress and software quality.
Paleontology: Theropod Dinosaurs and the Origin of Birds
University of Alberta (via Coursera)
Paleontology: Theropod Dinosaurs and the Origin of Birds is a five-lesson course teaching a comprehensive overview of the origins of birds. This course examines the anatomy, diversity, and evolution of theropod dinosaurs in relation to the origin of birds. Students explore various hypotheses for the origin of flight. Watch a preview of the course here: https://uofa.ualberta.ca/courses/paleontology-theropod-dinosaurs
Introduction to the Arctic: Climate
University of Alberta (via Coursera)
The University of Alberta, the University of Tromso and the University of the Arctic invite you to explore this four week course that examines the environment and climate of the circumpolar North. This course is the result of an international collaboration and provides you with an insight into our planet's North. Following an overview of regional geography, we will focus on the cryosphere (ice), as well as the atmosphere and ocean of the region. We will learn why the Arctic is cold and ice covered, and how that impacts its climate and ecosystems. We will also consider how the Arctic is connected to the rest of the world. Finally, we will examine present day climate change, the processes driving it, and evidence for it in the Arctic, before looking at the implications in the rapidly evolving North. Watch a preview of the course here: https://uofa.ualberta.ca/courses/arctic-climate
Sample-based Learning Methods
University of Alberta (via Coursera)
In this course, you will learn about several algorithms that can learn near optimal policies based on trial and error interaction with the environment---learning from the agent’s own experience. Learning from actual experience is striking because it requires no prior knowledge of the environment’s dynamics, yet can still attain optimal behavior. We will cover intuitively simple but powerful Monte Carlo methods, and temporal difference learning methods including Q-learning. We will wrap up this course investigating how we can get the best of both worlds: algorithms that can combine model-based planning (similar to dynamic programming) and temporal difference updates to radically accelerate learning. By the end of this course you will be able to: Understand Temporal-Difference learning and Monte Carlo as two strategies for estimating value functions from sampled experience Understand the importance of exploration, when using sampled experience rather than dynamic programming sweeps within a model Understand the connections between Monte Carlo and Dynamic Programming and TD. Implement and apply the TD algorithm, for estimating value functions Implement and apply Expected Sarsa and Q-learning (two TD methods for control) Understand the difference between on-policy and off-policy control Understand planning with simulated experience (as opposed to classic planning strategies) Implement a model-based approach to RL, called Dyna, which uses simulated experience Conduct an empirical study to see the improvements in sample efficiency when using Dyna
Physical Vitality in a Dynamic Workplace
University of Alberta (via Coursera)
This course gives you easy access to knowledge and tools that will allow you to develop a safe and healthy work environment for physical vitality. Whether you work from home, or an office, you'll understand the importance of physical vitality for delivering high-quality work. Explore and grasp concepts related to work-life balance, remote working, ergonomic effectiveness, and occupational health and safety.
Black Canadians: History, Presence, and Anti-Racist Futures
University of Alberta (via Coursera)
This micro-course explores some of the major histories, migrations, artists and activists that have contributed to the presence and survival of Black people in Canada. The course tracks Canada’s evolving relationship to Blackness and Black people, while inviting learners to reflect upon the ways Canadian views of race and multiculturalism have influenced Black communities throughout the country. We invite you to reflect, dream, and think alongside some of today’s most prominent Black intellectuals as we examine the history of Black presence in Canada, and imagine vibrant Black Canadian futures.
Bugs 101: Insect-Human Interactions
University of Alberta (via Coursera)
Of all the animals on earth, which are the strongest for their size? What about the fastest? Who were the first animals to evolve flight? Insects take all of these titles and more! As the most abundant animals on the planet, insects and other arthropods affect our lives in so many ways. From beneficial interactions like pollination and biological pest control, to the transmission of life threatening diseases; this course will teach you about the big ways that these little arthropods impact our lives. In Bugs 101: Insect-Human Interactions, you will be plunged into the diverse (and sometimes alien) world of arthropods to learn how they work, what they do, and how insects and humans interact every day. After completing this course, you will be able to: Describe the evolutionary relationships between insects and their arthropod relatives Inventory major groups of insects and their diversity Demonstrate evolutionary adaptations that make insects successful Discuss insect biology and human-insect interactions Evaluate positive and negative interactions between insects and humans Propose practical and symbolic roles insects play in human societies
21st Century Energy Transition: how do we make it work?
University of Alberta (via Coursera)
NOTE: “21 st Century Energy Transition – How do We Make it Work?” has been updated as of December 2024 to include new highlighting new ideas, technologies and important developments since its launch in October 2022. Affordable, abundant and reliable energy is fundamental to human well-being and prosperity. For the past 150 years, more and more people have gained access to energy, primarily in the form of fossil fuels – coal, petroleum and natural gas. But now, even while half of humanity cannot access adequate energy supplies, we are beginning a profound transition to more diverse energy sources. Climate change, environmental sustainability, and energy poverty are all important – and sometimes conflicting – drivers as we strive to supply more energy to more people with fewer negative impacts on Earth’s environments. In this course from the University of Alberta and Canadian Society for Evolving Energy, you will join us to learn about the many energy sources available, and where technology is providing exciting new solutions to energy and environmental challenges. Find out what roles energy storage must play to support the transition, and discuss how we can optimize transition processes. Examine competing viewpoints (“realities”) to enable energy transition, focusing on the practical challenges in bringing about change on a global basis. Finally, you will bring all these issues together to examine how the energy transition process is progressing and what we must do to create pathways to achieve our goals.
A Complete Reinforcement Learning System (Capstone)
University of Alberta (via Coursera)
In this final course, you will put together your knowledge from Courses 1, 2 and 3 to implement a complete RL solution to a problem. This capstone will let you see how each component---problem formulation, algorithm selection, parameter selection and representation design---fits together into a complete solution, and how to make appropriate choices when deploying RL in the real world. This project will require you to implement both the environment to stimulate your problem, and a control agent with Neural Network function approximation. In addition, you will conduct a scientific study of your learning system to develop your ability to assess the robustness of RL agents. To use RL in the real world, it is critical to (a) appropriately formalize the problem as an MDP, (b) select appropriate algorithms, (c ) identify what choices in your implementation will have large impacts on performance and (d) validate the expected behaviour of your algorithms. This capstone is valuable for anyone who is planning on using RL to solve real problems. To be successful in this course, you will need to have completed Courses 1, 2, and 3 of this Specialization or the equivalent. By the end of this course, you will be able to: Complete an RL solution to a problem, starting from problem formulation, appropriate algorithm selection and implementation and empirical study into the effectiveness of the solution.
Paleontology: Early Vertebrate Evolution
University of Alberta (via Coursera)
Paleontology: Early Vertebrate Evolution is a four-lesson course teaching a comprehensive overview of the origin of vertebrates. Students will explore the diversity of Palaeozoic lineages within a phylogenetic and evolutionary framework. This course examines the evolution of major vertebrate novelties including the origin of fins, jaws, and tetrapod limbs. Students also explore key Canadian fossil localities, including the Burgess Shale (British Columbia), Miguasha (Quebec), and Man On The Hill (Northwest Territories). Watch a preview of the course here: https://uofa.ualberta.ca/courses/paleontology-vertebrate-evolution
Science Literacy
University of Alberta (via Coursera)
Fake news or good science? In a world where we have access to unlimited information, it is hard to sift through the echo chamber of opinions fueled by emotions and personal biases, rather than scientific evidence. Science Literacy will teach you about the process of science, how to think critically, how to differentiate science from pseudoscience, how indigenous wisdom can inform science, how to understand and design a scientific study, and how to critically evaluate scientific communication in the media. Every module will build your new skill-base with real life examples, and at the end of each module you will have to apply these skills to scientific questions, talking points and controversies in the world. Warning: this course requires an open mind and the ability to self-reflect. In Science Literacy, you’ll hear from special guests: Timothy Caulfield, Canada Research Chair in Health Law and Policy and star of Netflix’s “A User's Guide to Cheating Death” on pseudoscience Dr. Torah Kachur, Scientist and CBC journalist on science communication (and miscommunication!) Christian Nelson, Citizen Scientist and creator of Edmonton Weather Nerdery, on experimental design Metis Elder Elmer Ghostkeeper and Cree Elder Kokum Rose Wabasca, on the holistic nature of Indigenous wisdom and how it can work with the scientific process Associate Professor in Psychology, Dr. David Rast on uncertainty and decision making
Introduction to Software Product Management
University of Alberta (via Coursera)
This course highlights the importance and role of software product management. It also provides an overview of the specialization, as well as its goals, structure, and expectations. The course explains the value of process, requirements, planning, and monitoring in producing better software.
Cognitive Vitality in a Dynamic Workplace
University of Alberta (via Coursera)
This course gives you easy access to knowledge and tools that will allow you to prioritize and strengthen mental health in a work environment. Whether you work from home, or an office, you'll understand the importance of cognitive vitality for delivering high-quality work. We will explore the foundations of mental health, learn to recognize signs of distress and develop effective communication and support strategies. Together, we will cultivate a workplace culture where employees feel safe, valued, and supported in their mental health journey. By the end of this course, you will possess the knowledge and tools to create a positive and inclusive environment where everyone can thrive.
Arctic Peoples and Cultures
University of Alberta (via Coursera)
Welcome to this online course – Peoples and cultures in the Arctic. In this, the 4th instalment of The Arctic MOOCs we want to bring you closer to peoples and cultures living in the circumpolar Arctic. Therefore, this is more like a documentary than a classical course. Our hope is that by getting to know people living in the Arctic you gain a better insight and understanding of what the Arctic means to thousands of individuals, but also that you, by acquiring more knowledge can become a valuable advocate for environmental and other issues facing the future of the Arctic. This is a collaboration between UArctic, University of Alberta, and UiT Arctic University of Norway.
Prediction and Control with Function Approximation
University of Alberta (via Coursera)
In this course, you will learn how to solve problems with large, high-dimensional, and potentially infinite state spaces. You will see that estimating value functions can be cast as a supervised learning problem---function approximation---allowing you to build agents that carefully balance generalization and discrimination in order to maximize reward. We will begin this journey by investigating how our policy evaluation or prediction methods like Monte Carlo and TD can be extended to the function approximation setting. You will learn about feature construction techniques for RL, and representation learning via neural networks and backprop. We conclude this course with a deep-dive into policy gradient methods; a way to learn policies directly without learning a value function. In this course you will solve two continuous-state control tasks and investigate the benefits of policy gradient methods in a continuous-action environment. Prerequisites: This course strongly builds on the fundamentals of Courses 1 and 2, and learners should have completed these before starting this course. Learners should also be comfortable with probabilities & expectations, basic linear algebra, basic calculus, Python 3.0 (at least 1 year), and implementing algorithms from pseudocode. By the end of this course, you will be able to: -Understand how to use supervised learning approaches to approximate value functions -Understand objectives for prediction (value estimation) under function approximation -Implement TD with function approximation (state aggregation), on an environment with an infinite state space (continuous state space) -Understand fixed basis and neural network approaches to feature construction -Implement TD with neural network function approximation in a continuous state environment -Understand new difficulties in exploration when moving to function approximation -Contrast discounted problem formulations for control versus an average reward problem formulation -Implem...
Fundamentals of Reinforcement Learning
University of Alberta (via Coursera)
Reinforcement Learning is a subfield of Machine Learning, but is also a general purpose formalism for automated decision-making and AI. This course introduces you to statistical learning techniques where an agent explicitly takes actions and interacts with the world. Understanding the importance and challenges of learning agents that make decisions is of vital importance today, with more and more companies interested in interactive agents and intelligent decision-making. This course introduces you to the fundamentals of Reinforcement Learning. When you finish this course, you will: Formalize problems as Markov Decision Processes Understand basic exploration methods and the exploration/exploitation tradeoff Understand value functions, as a general-purpose tool for optimal decision-making Know how to implement dynamic programming as an efficient solution approach to an industrial control problem This course teaches you the key concepts of Reinforcement Learning, underlying classic and modern algorithms in RL. After completing this course, you will be able to start using RL for real problems, where you have or can specify the MDP. This is the first course of the Reinforcement Learning Specialization.
Arctic Development
University of Alberta (via Coursera)
Welcome to Arctic: Development! In this third in a series of Arctic MOOCs, brought to you by a unique partnership between the University of Alberta and UiT The Arctic University of Norway, we will be exploring regional development in a changing arctic. In this 4-week course, you will investigate the role that natural resources play across the Indigenous, Nordic, Russian and North American Arctics, different strategies for resource management in different regions, and how these affect community planning and development efforts in an increasingly populated part of the world. We'll also see how climate change is dramatically impacting the Arctic, and examine a number of adaptations that different arctic communities are implementing to combat rapid, climate-influenced change. By the end of this course, you will have an idea of the opportunities presented to and difficulties faced by members of northern communities, and gain an understanding of just what regional development looks like in a changing Arctic.
Dino 101: Dinosaur Paleobiology
University of Alberta (via Coursera)
Dino 101: Dinosaur Paleobiology is a 12-lesson course teaching a comprehensive overview of non-avian dinosaurs. Topics covered: anatomy, eating, locomotion, growth, environmental and behavioral adaptations, origins and extinction. Lessons are delivered from museums, fossil-preparation labs and dig sites. Estimated workload: 3-5 hrs/week.
Service-Oriented Architecture
University of Alberta (via Coursera)
Based on an understanding of architectural styles, you will review architectures for web applications, then explore the basics of Service-Oriented Architecture (SOA) in two approaches: Web Services (WS) and Representational State Transfer (REST) architecture. In the Capstone Project you will connect a Java-based Android application with Elasticsearch, a web service with a REST application programmer interface (API). After completing this course, you will be able to: • Describe SOA (Service-Oriented Architecture) to structure web-based systems. • Explain WS services (i.e., SOAP over HTTP, WSDL, UDDI, BPEL). • Apply REST architecture (i.e., JSON over HTTP, URI). • Identify REST design principles. • Create a system using REST interfaces. • Apply microservice architecture.
Mountains 101
University of Alberta (via Coursera)
Mountains 101 is a broad and integrated overview of the mountain world. This 12-lesson course covers an interdisciplinary field of study focusing on the physical, biological, and human dimensions of mountain places in Alberta, Canada, and around the world. Specifically, we'll study the geological origins of mountains, how they’re built-up and worn-down over time; we’ll learn about their importance for biodiversity and water cycles, globally and locally; we’ll explore their cultural significance to societies around the globe, and how that relationship has evolved over time; and we’ll learn how mountains are used, how they’re protected, and how today they’re experiencing rapid change in a warming climate. At the end of each lesson, Mountains 101 will also provide learners with some smart tricks -- Tech Tips -- to safely enjoy time in the high alpine environment: from how to pick the best footwear for hiking to making smart decisions in avalanche terrain. We’ll be delivering your online lessons from valley bottoms to mountaintops, from museums and labs, to alpine huts and other spectacular alpine sites, and we’ll do so with the help of a whole host of experts. We invite you to join us for this online adventure! The mountains are calling...
Design Patterns
University of Alberta (via Coursera)
This course extends object-oriented analysis and design by incorporating design patterns to create interactive applications. Through a survey of established design patterns, you will gain a foundation for more complex software applications. Finally, you will identify problematic software designs by referencing a catalog of code smells. You will be challenged in the Capstone Project to redesign an existing Java-based Android application to implement a combination of design patterns. You will also critique a given Java codebase for code smells. After completing this course, you will be able to: • Demonstrate how to use design patterns to address user interface design issues. • Identify the most suitable design pattern to address a given application design problem. • Apply design principles (e.g., open-closed, dependency inversion, least knowledge). • Critique code by identifying and refactoring anti-patterns. • Apply the model-view-controller architectural pattern.