Deep Reinforcement Learning
Combine the power of Reinforcement Learning with Deep Learning to solve complex problems in various domains
Classes : 30 Days : 6 months Duration : Weekdays / Weekends
Today, some of the top AI models integrate deep learning. They form a new branch of AI called Deep Reinforcement Learning (DRL).
At Vyom Data Sciences, we feel proud to present you such an advanced training to start your endeavour towards an exciting journey for deep reinforcement learning, the very basis for AI and Robotics.
There are five parts that constitute the general AI framework, or AI Blueprint, that should be followed whenever you build an environment to solve any business problem with deep reinforcement learning. During this DRL training, you got to build all these five parts individually and the whole as well.
In the end, what matters is that you are able to build a DRL model for a real-world business problem. The environment itself is less important; whats most important is that you know how to connect a deep reinforcement learning model to an environment, and how to train the model inside.
By the end of this hands-on training, students shall be able to:
-Explain the core concepts of Deep Reinforcement Learning
-Create general AI blueprint when building a DRL model
-Formalize problems as Markov decision processes
-Implement dynamic programming algorithms for solving small DRL problems
-Understand the principles of value-based and policy-based DRL algorithms
-Apply DRL algorithms to solve real-world problems using Python
-Evaluate the performance of DRL 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 Deep Reinforcement Learning.
Trainers:
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 DRL, AI, Robotics
- PhD students who wish to incorporate DRL, AI, Robotics techniques in their research
- Programmers who want to specialize in DRL, AI and Robotics
- DRL, AI Scientists and Researchers
-Python Programming
-Familiarity with mathematical concepts such as probability, linear algebra, and calculus
-Basics of machine learning and neural networks
-Fundamentals of reinforcement learning
- Module 1: Introduction to Reinforcement Learning
- Module 2: Deep Learning Basics for RL
- Module 3: Advanced DRL Algorithms
- Module 4: Exploration vs. Exploitation
- Module 5: Continuous Action Spaces and Applications
- Module 6: Model-Based Reinforcement Learning
- Module 7: Multi-Agent Reinforcement Learning
- Module 8: Ethics and Challenges in DRL
- Module 9: Real-World Applications and Case Studies
- Module 10: Capstone Project
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Student Reviews
Bhawana
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.
Harish
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.