Title
In this course, you will be introduced to Reinforcement Learning, an area of Machine Learning. You will learn the Markov Decision Processes, Bandit Algorithms, Dynamic Programming, and Temporal Difference (TD) methods. You will be introduced to Value function, Bellman Equation, and Value iteration. You will also learn Policy Gradient methods. You will learn to make decisions in uncertain environment.
| Jul 25 | Sat,Sun (4 Weeks) Weekend Batch | Filling Fast 02:30 PM 04:30 PM |
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In this course, you will be introduced to Reinforcement Learning, an area of Machine Learning. You will learn the Markov Decision Processes, Bandit Algorithms, Dynamic Programming, and Temporal Difference (TD) methods. You will be introduced to Value function, Bellman Equation, and Value iteration. You will also learn Policy Gradient methods. You will learn to make decisions in uncertain environment.
Who should go for this training?
Pre-requisites
Fundamentals in AI & ML, Probability, Python, Neural Networks, Frameworks, Deep Learning library like PyTorch/ Theano/ Tensorflow
reinforcementlearning, Artificial Intelligence, TensorFlow, CNN, Bandit Algorithms, Markov Decision Process, Markov Decision Process, Markov Reward Process, Dynamic Programming, Temporal Difference Methods, Monte Carlo Methods, Deep Q Learning, Policy Gradients
Learning Objectives: The aim of this module is to introduce you to the fundamentals of Reinforcement Learning and its elements. This module also introduces you to OpenAI Gym - a programming environment used for implementing RL agents.
Topics:
Structure your learning and get a certificate to prove it.
What are the system requirements for this Reinforcement Learning Certification Training
The system requirement is a system with an Intel i3 processor or above, minimum 3GB RAM (4GB recommended) and an operating system either of 32bit or 64bit.
How will I execute practicals in this Reinforcement Learning Certification Training?
Cloud Lab has been provided to ensure you get real-time hands-on experience to practice your new skills on a pre-configured environment.
Which project will be part of this StepLeaf's Reinforcement Learning Online Training Course?
Project Statement: Train an RL Agent to win a Game
Description:
Using a given Environment in OpenAI Gym, train an RL Agent to accomplish a predefined task. In this project, you will be creating a Neural Network, and applying Policy Gradient Algorithm to train the Agent.
Certification
StepLeaf’s Reinforcement Learning Certificate Holders works at 1000s of MNC Companies All Over the World
All the instructors at StepLeaf are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are trained by StepLeaf for providing an awesome learning experience to the participants.