Reinforcement Learning

Reinforcement Learning


A fun and hands-on introduction to RL with Python, enabling you to create intelligent machines and Deep RL

Classes : 30                  Days : 6 months                  Duration : Weekdays / Weekends

When people refer to AI today, some of them think of Machine Learning, while others think of Reinforcement Learning (RL). Reinforcement learning is another approach to machine learning alongside supervised learning and unsupervised Learning. If AI is the science that tries to mimic Human Intelligence, then RL is the closest match to the way we think.

This hands-on training provides a comprehensive introduction to Reinforcement Learning, a powerful AI paradigm that enables agents to learn by interacting with their environment. The training covers the fundamental concepts of RL, including Markov Decision Processes (MDPs), value functions, policy optimization, and exploration-exploitation tradeoff. Students will also gain hands-on experience with implementing RL algorithms using popular Python libraries.

By the end of this hands-on training, students shall be able to:

-Explain the core concepts of reinforcement learning
-Formalize problems as Markov decision processes
-Implement dynamic programming algorithms for solving small RL problems
-Understand the principles of value-based and policy-based RL algorithms
-Apply RL algorithms to solve real-world problems using Python
-Evaluate the performance of RL algorithms and identify potential challenges

This training has been designed by experienced Data Scientists who will help you to understand the WHYs and HOWs of Reinforcement Learning.

Experts from the field of Maths, Data Science and Management, each with over 25 years of International experience working in EU/US/Australia

Who this training is for:
- Students who want to get started in AI, Robotics
- PhD students who wish to incorporate AI, Robotics techniques in their research
- Programmers who want to specialize in AI and Robotics
- AI Scientists and Researchers

-Basic programming skills in Python
-Familiarity with mathematical concepts such as probability, linear algebra, and calculus
-Familiarity with Machine Learning Algorithms

-Module 1: Introduction to Reinforcement Learning
-Module 2: Markov Decision Processes (MDPs)
-Module 3: Value-Based Reinforcement Learning
-Module 4: Policy-Based Reinforcement Learning
-Module 5: Temporal Difference Learning
-Module 6: Exploration and Exploitation Strategies
-Module 7: Introduction to Deep Reinforcement Learning
-Module 8: Advanced Topics in Reinforcement Learning
-Module 9: Applications of Reinforcement Learning


Fabulous NLP + ML course

I have eleven plus years of experience taking training courses. I do not usually complete surveys.
Your instructor was excellent, the best I've experienced on a software subject, and I couldn't imagine him doing a better job of seamlessly walking students through a breadth of information for such complex subject like AI and ML. he did a fabulous job pacing everything and addressing student questions. I am very impressed.


Excellent ML course!

The course was well structured and easy to understand. Good pace of learning.
The institute believes to provide knowledge as well as guidance in detail to each & every student.
I completed my ML course from the institute. Their international exp does help a lot !
Thanks for the training sir.

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