A Complete Reinforcement Learning System (Capstone)
In this final course, you will put together your knowledge from Courses 1, 2 and 3 to implement a complete RL solution to a problem. This capstone will let you see how each component—problem formulation, algorithm selection, parameter selection and representation design—fits together into a complete solution, and how to make appropriate choices when deploying RL in the real world. This project will require you to implement both the environment to stimulate your problem, and a control agent with Neural Network function approximation. In addition, you will conduct a scientific study of your learning system to develop your ability to assess the robustness of RL agents. To use RL in the real world, it is critical to (a) appropriately formalize the problem as an MDP, (b) select appropriate algorithms, (c ) identify what choices in your implementation will have large impacts on performance and (d) validate the expected behaviour of your algorithms. This capstone is valuable for anyone who is planning on using RL to solve real problems.To be successful in this course, you will need to have completed Courses 1, 2, and 3 of this Specialization or the equivalent.
By the end of this course, you will be able to:
Complete an RL solution to a problem, starting from problem formulation, appropriate algorithm selection and implementation and empirical study into the effectiveness of the solution.
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Syllabus
Syllabus - What you will learn from this course
Week 1
Welcome to the Final Capstone Course!
Week 2
Milestone 1: Formalize Word Problem as MDP
Week 3
Milestone 2: Choosing The Right Algorithm
Week 4
Milestone 3: Identify Key Performance Parameters
Week 5
Milestone 4: Implement Your Agent
Week 6
Milestone 5: Submit Your Parameter Study!
FAQ
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
Reviews
Project could be better designed and could be made more fun. The first 3 courses were brilliant. I finished the entire capstone in less than 26-hours to save money!
Good project as a capstone. Wish there would have been more work needed from our side of things in terms of coding, but very solid final course for RL.
The last course of the specialization provides full implementation of built knowledge by the previous lessons so it is well designed for the capstone project.
The course is applicative in real world projects. I think it is a very good choice for any one that is interested to learn how to apply reinforcement learning.
