About this Course

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Learner Career Outcomes

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started a new career after completing these courses
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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. 15 hours to complete
English

What you will learn

  • 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

Skills you will gain

Artificial Intelligence (AI)Machine LearningReinforcement LearningFunction ApproximationIntelligent Systems

Learner Career Outcomes

14%

started a new career after completing these courses
Shareable Certificate
Earn a Certificate upon completion
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. 15 hours to complete
English

Offered by

Placeholder

University of Alberta

Placeholder

Alberta Machine Intelligence Institute

Syllabus - What you will learn from this course

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Week
1

Week 1

1 hour to complete

Welcome to the Course!

1 hour to complete
4 videos (Total 20 min), 2 readings
4 hours to complete

An Introduction to Sequential Decision-Making

4 hours to complete
8 videos (Total 46 min), 3 readings, 2 quizzes
Week
2

Week 2

3 hours to complete

Markov Decision Processes

3 hours to complete
7 videos (Total 36 min), 2 readings, 2 quizzes
Week
3

Week 3

3 hours to complete

Value Functions & Bellman Equations

3 hours to complete
9 videos (Total 56 min), 3 readings, 2 quizzes
Week
4

Week 4

4 hours to complete

Dynamic Programming

4 hours to complete
10 videos (Total 72 min), 3 readings, 2 quizzes

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About the Reinforcement Learning Specialization

Reinforcement Learning

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