Reinforcement Learning Online Course | Edureka
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Reinforcement Learning

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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.


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Why should you take Reinforcement Learning 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

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
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
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
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
    Goal: The aim of this module is to provide you hands-on experience in Reinforcement Learning.
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Structure your learning and get a certificate to prove it.
    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.
  • Web Developers
  • Software Developers
  • Programmers
  • Anyone who wants to learn reinforcement learning
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
5000 Total number of reviews
4.57 Aggregate review score
80% Course completion rate
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    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.
    Cloud Lab has been provided to ensure you get real-time hands-on experience to practice your new skills on a pre-configured environment.

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.

Assignments

Each class will be followed by practical assignments.

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 sharing.

Cloud Lab New

Cloud Lab has been provided to ensure you get real-time hands-on experience to practice your new skills on a pre-configured environment
"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."

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.

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 the access to our 24x7 support team will be granted instantly as well. You can start learning right away.

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

For payments done using credit cards, to make this a No Cost EMI offer, the interest amount will be discounted from the price of the course. Your card will be charged for the course price minus the discounted interest. The total amount you will pay to the bank (excluding GST) will be equal to the price of the course. The bank will charge GST on the interest amount. For payments done using Razor Pay EMI, the price will not be discounted upfront. Instead, you will not be charged any interest for a No Cost EMI offer.
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