Master reinforcement learning concepts and implement AI solutions for real-world problems. Learn from University of Alberta experts.
Master reinforcement learning concepts and implement AI solutions for real-world problems. Learn from University of Alberta experts.
This comprehensive specialization teaches you the foundations of modern probabilistic artificial intelligence through reinforcement learning. Across four courses, you'll learn to build complete RL solutions for sequential decision-making problems. The program covers essential algorithms including Temporal-Difference learning, Monte Carlo, Sarsa, Q-learning, and Policy Gradients. You'll gain practical experience through programming assignments and learn to apply these techniques to real-world applications in game development, customer interaction, smart assistants, and industrial control systems.
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English
বাংলা, پښتو, اردو, 2 more
What you'll learn
Build complete reinforcement learning systems for sequential decision making
Master various RL algorithms including TD learning, Monte Carlo, and Q-learning
Implement neural network function approximation for RL problems
Understand how to formalize tasks as reinforcement learning problems
Apply RL solutions to real-world applications and industrial problems
Develop expertise in policy gradient methods and actor-critic architectures
Skills you'll gain
This course includes:
80 Hours PreRecorded video
Programming assignments, Quizzes, Capstone Project
Access on Mobile
FullTime access
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There are 4 courses in this program
Valuation for Startups Using Discounted Cash Flows Approach
Course 1 · 8 Hours to complete · 4 modules
International Entertainment and Sports Marketing
Course 2 · 11 Hours to complete · 3 modules
AWS: Application Integration and Networking
Course 3 · 5 Hours to complete · 2 modules
AWS: Security, Governance, and Compliance
Course 4 · 4 Hours to complete · 2 modules
Fee Structure
Payment options
Financial Aid
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