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Home   >    All Courses   >   Artificial Intelligence   >   Reinforcement Learning

Reinforcement Learning

SUPPORT NO. +1 302 956 2015 (USA)

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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.

Why this course ?


It is predicted that about $47 billion will be budgeted towards machine learning in 2020 – Analyticsinsight.net
The average salary for a Machine Learning Engineer is $1,18,452 – Glassdoor.co
Machine Learning Engineers rank among the top emerging jobs on LinkedIn

  • 15K + satisfied learners. Reviews

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Instructor-led Sessions

15 Hours of Online Live Instructor-Led Classes. Weekend Class : 5 sessions of 3 hours each.

Real-life Case Studies

Live project based on any of the selected use cases, involving implementation of the various Reinforcement Learning concepts.

Lifetime Access

You get lifetime access to Learning Management System (LMS) where presentations, quizzes, installation guide & class recordings are there.

24 x 7 Expert Support

We have 24x7 online support team to resolve all your technical queries, through ticket based tracking system, for the lifetime.

Certification

Towards the end of the course, Edureka certifies you as a "Reinforcemnt Learning Professional" based on the project you submit.

Forum

We have a community forum for all our customers that further facilitates learning through peer interaction and knowledge

Real-life Case Studies

Live project based on any of the selected use cases, involving implementation of the various Graphical Models concepts.

   About Reinforcement Learning Course

    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?

  • Web Developers
  • Software Developers
  • Programmers
  • Anyone who wants to learn reinforcement learning

   What are the pre-requisites for this Course?

Required Pre-requisites
  • Fundamentals in AI & ML, Probability, Python, Neural Networks, Frameworks, Deep Learning library like PyTorch/ Theano/ Tensorflow
Edureka offers you complimentary self-paced courses
  • Statistics and Machine learning algorithms
  • Python Essentials

   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 Edureka'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.

   Introduction to Reinforcement Learning

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:
  • Branches of Machine Learning
  • What is Reinforcement Learning?
  • The Reinforcement Learning Process
  • Elements of Reinforcement Learning
  • RL Agent Taxonomy
  • Reinforcement Learning Problem
  • Introduction to OpenAI Gym

   Bandit Algorithms and Markov Decision Process

Learning Objectives: The aim of this module is to learn Bandit Algorithms and Markov Decision Process.

Topics:
  • Bandit Algorithms
  • Markov Process
  • Markov Reward Process
  • Markov Decision Process

   Dynamic Programming & Temporal Difference Methods

Learning Objectives: The aim of this module is to develop an understanding of Dynamic Programming Algorithms and Temporal Difference Learning methods.

Topics:

  • Introduction to Dynamic Programming
  • Dynamic Programming Algorithms
  • Monte Carlo Methods
  • Temporal Difference Learning Methods

   Deep Q Learning

Learning Objectives: The aim of this module is to learn Policy Gradients and develop an understanding of Deep Q Learning

Topics:
  • Policy Gradients
  • Policy Gradients using TensorFlow
  • Deep Q learning
  • Q learning with replay buffers, target networks, and CNN

   In-class Project

    Goal: The aim of this module is to provide you hands-on experience in Reinforcement Learning.

   What if I miss a class?

You will never miss a lecture at Edureka! You can choose either of the two options:

  • View the recorded session of the class available in your LMS.
  • You can attend the missed session, in any other live batch.

   What if I have queries after I complete this course?

Your access to the Support Team is for lifetime and will be available 24/7. The team will help you in resolving queries, during and after the course.

   How soon after signing up would I get access to the learning content?

Post-enrolment, the LMS access will be instantly provided to you and will be available for lifetime. You will be able to access the complete set of previous class recordings, PPTs, PDFs, assignments. Moreover, access to our 24x7 support team will be granted instantly as well. You can start learning right away.

   Is the course material accessible to the students even after the course training is over?

Yes, the access to the course material will be available for lifetime once you have enrolled into the course.

   Is the course material accessible to the students even after the course training is over?

Yes, the access to the course material will be available for lifetime once you have enrolled into the course.