About this Course
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Start instantly and learn at your own schedule.

Flexible deadlines

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Intermediate Level

Probabilities & Expectations, basic linear algebra, basic calculus, Python 3.0 (at least 1 year), implementing algorithms from pseudocode

Approx. 21 hours to complete

Suggested: 4-6 hours/week...

English

Subtitles: English

Skills you will gain

Artificial Intelligence (AI)Machine LearningReinforcement LearningFunction ApproximationIntelligent Systems

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Probabilities & Expectations, basic linear algebra, basic calculus, Python 3.0 (at least 1 year), implementing algorithms from pseudocode

Approx. 21 hours to complete

Suggested: 4-6 hours/week...

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1
1 hour to complete

Welcome to the Course!

2 videos (Total 10 min), 2 readings
2 videos
Instructor Introductions8m
2 readings
Reinforcement Learning Textbook10m
Read Me: Pre-requisites and Learning Objectives10m
Week
2
3 hours to complete

Monte Carlo Methods for Prediction & Control

10 videos (Total 46 min), 2 readings, 1 quiz
10 videos
Using Monte Carlo for Prediction6m
Using Monte Carlo for Action Values2m
Using Monte Carlo methods for generalized policy iteration2m
Solving the Blackjack Example3m
Epsilon-soft policies5m
Why does off-policy learning matter?4m
Importance Sampling4m
Off-Policy Monte Carlo Prediction5m
Week 1 Summary3m
2 readings
Weekly Reading40m
Chapter Summary40m
1 practice exercise
Graded Quiz
Week
3
6 hours to complete

Temporal Difference Learning Methods for Prediction

4 videos (Total 18 min), 1 reading, 2 quizzes
4 videos
The advantages of temporal difference learning5m
Comparing TD and Monte Carlo5m
Week 2 Summary2m
1 reading
Weekly Reading40m
1 practice exercise
Practice Quiz30m
Week
4
8 hours to complete

Temporal Difference Learning Methods for Control

9 videos (Total 30 min), 2 readings, 2 quizzes
9 videos
Sarsa in the Windy Grid World3m
What is Q-learning?3m
Q-learning in the Windy Grid World3m
How is Q-learning off-policy?4m
Expected Sarsa3m
Expected Sarsa in the Cliff World3m
Generality of Expected Sarsa1m
Week 3 Summary2m
2 readings
Weekly Reading40m
Chapter summary40m
1 practice exercise
Practice Quiz18m

Instructors

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Martha White

Assistant Professor
Computing Science
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Adam White

Assistant Professor
Computing Science

About University of Alberta

UAlberta is considered among the world’s leading public research- and teaching-intensive universities. As one of Canada’s top universities, we’re known for excellence across the humanities, sciences, creative arts, business, engineering and health sciences....

About Alberta Machine Intelligence Institute

The Alberta Machine Intelligence Institute (Amii) is home to some of the world’s top talent in machine intelligence. We’re an Alberta-based research institute that pushes the bounds of academic knowledge and guides business understanding of artificial intelligence and machine learning....

About the Reinforcement Learning Specialization

The Reinforcement Learning Specialization consists of 4 courses exploring the power of adaptive learning systems and artificial intelligence (AI). Harnessing the full potential of artificial intelligence requires adaptive learning systems. Learn how Reinforcement Learning (RL) solutions help solve real-world problems through trial-and-error interaction by implementing a complete RL solution from beginning to end. By the end of this Specialization, learners will understand the foundations of much of modern probabilistic artificial intelligence (AI) and be prepared to take more advanced courses or to apply AI tools and ideas to real-world problems. This content will focus on “small-scale” problems in order to understand the foundations of Reinforcement Learning, as taught by world-renowned experts at the University of Alberta, Faculty of Science. The tools learned in this Specialization can be applied to game development (AI), customer interaction (how a website interacts with customers), smart assistants, recommender systems, supply chain, industrial control, finance, oil & gas pipelines, industrial control systems, and more....
Reinforcement Learning

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

More questions? Visit the Learner Help Center.