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Reinforcement Learning Specialization
Master reinforcement learning concepts and implement AI solutions for real-world problems. Learn from University of Alberta experts.
Course Cost
₹ 5,199
Intermediate
Skill Level
73 Hours
Self-paced lessons
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.
56,593 Enrolled
English
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56,593 Enrolled
English
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:
73 Hours PreRecorded video
Programming assignments, Quizzes, Capstone Project
Access on Mobile
FullTime access
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There are 4 courses in this program
Fundamentals of Reinforcement Learning
Course 1 · 13 Hours to complete · 5 modules
Sample-based Learning Methods
Course 2 · 21 Hours to complete · 5 modules
Prediction and Control with Function Approximation
Course 3 · 20 Hours to complete · 5 modules
A Complete Reinforcement Learning System (Capstone)
Course 4 · 15 Hours to complete · 6 modules
Fee Structure
Payment options
Financial Aid
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