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Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery
English	Self Study	Video and Text Based

Course Overview

The course Fundamentals of Reinforcement Learning certification course is offered by Coursera by collaboration with the University of Alberta to make the aspirants skilful with machine learning and applications of Artificial Intelligence. The course is free to enrol and can access all the course materials free of cost. Therefore aspirants can use the opportunity for growing their career with a course completion certificate and increase the chances of hiring.

With the digital connection over the world, Business Intelligence over decision making is made essential in organizations. Decision making increases the prosperity of the business. Therefore the use of decision making with Artificial Intelligence and machine learning became most popular when the programme comes into existence. Organizations are looking forward to candidates who are skilled in this type of Artificial Intelligence, Robotics, Machine learning and, the Internet of things (IoT) as well

Coursera is the digital platform to learn the concepts that are offered for free. Candidates can learn throughout their lifetime and can avail of certificates after completion of the Fundamentals of Reinforcement Learning Training course.

The Highlights

Offered by University of Alberta
Offered by Alberta Machine Intelligence Institute
Approximately 15 hours to complete the course
Certification by Coursera
Availability in different language subtitles

Programme Offerings

Study Materials
Online video lectures
quizzes
Mobile access
assignments
practice assessments
Exercises

Courses and Certificate Fees

Certificate Availability	Certificate Providing Authority
yes	Coursera

Fee details for the Fundamentals of Reinforcement Learning certification fee are as follows:

No refund fee is issued in any cause
If the candidate does not use the account after the fee payment for 180 days then the candidate cannot access the course and if need a certificate then he/she should pay the fee again.

Fundamentals of Reinforcement Learning Fee Structure

Description	Amount
Course Fee, 1 Month	Rs. 6,451
Course Fee, 3 Months	Rs. 12,903
Course Fee, 6 Months	Rs. 19,354

Eligibility Criteria

Certificate qualifying details

It is mandatory for the candidate to complete the course and submit all the assignments in the given time to get the certificate. Otherwise, no certificate will be awarded to the candidate. Also, the candidate will be given a Fundamentals of Reinforcement Learning certification by Coursera only if he/she pays the fee. Or else the candidate can learn the course without a certificate for free.

What you will learn

Decision making skillsMachine learningKnowledge of Artificial Intelligence

Once the Fundamentals of Reinforcement Learning certification syllabus is pursued by the candidates, they will learn and master different concepts that are mentioned below:

Dynamic programming to optimize the costs and maximizing the profits in sales and marketing
Decision processes about the techniques of deciding during risks
Decision making to choose the best among different alternatives

Who it is for

Software DeveloperData AnalystData ScientistMachine Learning Engineer

The Fundamentals of Reinforcement Learning programme shall be ideal for those who are keen on becoming ML Engineers.

Admission Details

Application form details for Fundamentals of Reinforcement Learning classes are as follows:

Step 1: Visit the website https://www.coursera.org/learn/fundamentals-of-reinforcement-learning

and click on enroll now button

Step 2: Candidate will be asked to choose the type of course namely course with or without certification and then click continue

Step 3: the candidate will be asked to register or fill in all the relevant details and if the candidate needs a certificate he/she should pay and he is taken to the payment gateway and the fee is paid online

Step 4: Next candidate will be confirmed if he/she is eligible for financial aid or not by email.

Step 5: Thereby candidate receives a confirmation message and they can continue the course

The Syllabus

Videos

Specialization Introduction
Course Introduction
Meet your instructors!
Your Specialization Roadmap

Readings

Reinforcement Learning Textbook
Read Me: Pre-requisites and Learning Objectives

Videos

Sequential Decision Making with Evaluative Feedback
Learning Action Values
Estimating Action Values Incrementally
What is the trade-off?
Optimistic Initial Values
Upper-Confidence Bound (UCB) Action Selection
Jonathan Langford: Contextual Bandits for Real World Reinforcement Learning
Week 1 Summary

Readings

Module 1 Learning Objectives
Weekly Reading
Chapter Summary

Practice exercises

Sequential Decision-Making

Videos

Markov Decision Processes
Examples of MDPs
The Goal of Reinforcement Learning
Michael Littman: The Reward Hypothesis
Continuing Tasks
Examples of Episodic and Continuing Tasks
Week 2 Summary

Readings

Module 2 Learning Objectives
Weekly Reading

Practice exercises

MDPs

Videos

Specifying Policies
Value Functions
Rich Sutton and Andy Barto: A brief History of RL
Bellman Equation Derivation
Why Bellman Equations?
Optimal Policies
Optimal Value Functions
Using Optimal Value Functions to Get Optimal Policies
Week 3 Summary

Readings

Module 3 Learning Objectives
Weekly Reading
Chapter Summary

Practice exercises

[Practice] Value Functions and Bellman Equations
Value Functions and Bellman Equations

Videos

Policy Evaluation vs. Control
Iterative Policy Evaluation
Policy Improvement
Policy Iteration
Flexibility of the Policy Iteration Framework
Efficiency of Dynamic Programming
Warren Powell: Approximate Dynamic Programming for Fleet Management (Short)
Warren Powell: Approximate Dynamic Programming for Fleet Management (Long)
Week 4 Summary
Congratulations!

Readings

Module 4 Learning Objectives
Weekly Reading
Chapter Summary

Practice exercises

Dynamic Programming

Instructors

University of Alberta, Edmonton Frequently Asked Questions (FAQ's)

1: How can I avail certificate?

Candidates can avail of the certificate by completing the course and submitting all the assignments of the course. Also, candidates should pay the fee in order to get the certificate.

2: Can working professionals enroll in the course?

Yes, Everyone can enrol in the course. They can be students, freshers, professionals. Coursera does not require any pre-requisites to get into the course

3: How can I use the course certificate?

The certificate given by Coursera is digital and shareable. Hence the certificate can increase the chances of the candidate getting hired in top MNCs.

4: Can I get job assistance training?

No, Coursera cannot give job assistance training to the candidates. But it can make the candidates capable of getting the job and skills they require with conceptual wise learning.

5: How can I get financial aid for the Fundamentals of Reinforcement Learning online course?

Financial aid is given to candidates who cannot afford financially and there should be a proper reason to get financial aid. Therefore every candidate is no application for this benefit.