About this Course

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Learner Career Outcomes

33%

started a new career after completing these courses

22%

got a tangible career benefit from this course

25%

got a pay increase or promotion
Flexible deadlines
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Shareable Certificate
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100% online
Start instantly and learn at your own schedule.
Intermediate Level

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

Approx. 22 hours to complete
English

Skills you will gain

Artificial Intelligence (AI)Machine LearningReinforcement LearningFunction ApproximationIntelligent Systems

Learner Career Outcomes

33%

started a new career after completing these courses

22%

got a tangible career benefit from this course

25%

got a pay increase or promotion
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Intermediate Level

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

Approx. 22 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
2 videos (Total 10 min), 2 readings
3 hours to complete

Monte Carlo Methods for Prediction & Control

3 hours to complete
11 videos (Total 58 min), 3 readings, 2 quizzes
Week
2

Week 2

5 hours to complete

Temporal Difference Learning Methods for Prediction

5 hours to complete
6 videos (Total 37 min), 2 readings, 2 quizzes
Week
3

Week 3

6 hours to complete

Temporal Difference Learning Methods for Control

6 hours to complete
9 videos (Total 30 min), 3 readings, 2 quizzes
Week
4

Week 4

7 hours to complete

Planning, Learning & Acting

7 hours to complete
11 videos (Total 47 min), 4 readings, 2 quizzes

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About the Reinforcement Learning Specialization

Reinforcement Learning

Frequently Asked Questions

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