À propos de ce cours

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Dates limites flexibles
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Niveau intermédiaire

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

Approx. 28 heures pour terminer
Anglais
Sous-titres : Anglais

Compétences que vous acquerrez

Artificial Intelligence (AI)Machine LearningReinforcement LearningFunction ApproximationIntelligent Systems
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Niveau intermédiaire

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

Approx. 28 heures pour terminer
Anglais
Sous-titres : Anglais

Offert par

Logo Université de l'Alberta

Université de l'Alberta

Logo Alberta Machine Intelligence Institute

Alberta Machine Intelligence Institute

Programme du cours : ce que vous apprendrez dans ce cours

Évaluation du contenuThumbs Up92%(1,986 notes)Info
Semaine
1

Semaine 1

1 heure pour terminer

Welcome to the Course!

1 heure pour terminer
2 vidéos (Total 10 min), 2 lectures
2 vidéos
Meet your instructors!8 min
2 lectures
Reinforcement Learning Textbook10 min
Read Me: Pre-requisites and Learning Objectives10 min
Semaine
2

Semaine 2

4 heures pour terminer

Monte Carlo Methods for Prediction & Control

4 heures pour terminer
11 vidéos (Total 58 min), 2 lectures, 1 quiz
11 vidéos
Using Monte Carlo for Prediction6 min
Using Monte Carlo for Action Values2 min
Using Monte Carlo methods for generalized policy iteration2 min
Solving the Blackjack Example3 min
Epsilon-soft policies5 min
Why does off-policy learning matter?4 min
Importance Sampling4 min
Off-Policy Monte Carlo Prediction5 min
Emma Brunskill: Batch Reinforcement Learning12 min
Week 1 Summary3 min
2 lectures
Weekly Reading40 min
Chapter Summary40 min
1 exercice pour s'entraîner
Graded Quiz30 min
Semaine
3

Semaine 3

6 heures pour terminer

Temporal Difference Learning Methods for Prediction

6 heures pour terminer
6 vidéos (Total 37 min), 1 lecture, 2 quiz
6 vidéos
Rich Sutton: The Importance of TD Learning6 min
The advantages of temporal difference learning5 min
Comparing TD and Monte Carlo5 min
Andy Barto and Rich Sutton: More on the History of RL12 min
Week 2 Summary2 min
1 lecture
Weekly Reading40 min
1 exercice pour s'entraîner
Practice Quiz30 min
Semaine
4

Semaine 4

8 heures pour terminer

Temporal Difference Learning Methods for Control

8 heures pour terminer
9 vidéos (Total 30 min), 2 lectures, 2 quiz
9 vidéos
Sarsa in the Windy Grid World3 min
What is Q-learning?3 min
Q-learning in the Windy Grid World3 min
How is Q-learning off-policy?4 min
Expected Sarsa3 min
Expected Sarsa in the Cliff World3 min
Generality of Expected Sarsa1 min
Week 3 Summary2 min
2 lectures
Weekly Reading40 min
Chapter summary40 min
1 exercice pour s'entraîner
Practice Quiz30 min

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À propos du Spécialisation Apprentissage par renforcement

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....
Apprentissage par renforcement

Foire Aux Questions

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  • 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.

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