- Course 4 Introduction
- Reinforcement Learning Textbook
- Meet the Instructors
- Learning objectives and prerequisites
A Complete Reinforcement Learning System (Capstone)
The certification course in A Complete Reinforcement Learning System (Capstone) will help you understand RL and solve various RL problems in the real world.
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based
The Reinforcement Learning System (Capstone) certification course is a part of the ‘Reinforcement Learning Specialisation’ programme available on Coursera. This course is the 4th and final course in the series and aims to provide the students with complete practical knowledge on how to carry out Reinforcement Learning solutions in the real world.
In the Reinforcement Learning System (Capstone) online course, students will gain well-rounded and application-based skills that will help them in implementing Reinforcement Learning. They will complete the entire Reinforcement Learning problem-solving process – starting with the formulation of a problem, assessing the appropriate algorithm for the problem, and validating the impacts of the algorithm.
The Reinforcement Learning System (Capstone) programme by Coursera is suited for anyone who is expected to perform RL solutions in their field, along with the knowledge of skills like Machine Learning and Reinforcement Learning. The candidates will delve deep into the formalisation of a problem and how to translate it into an MDP. Finally, they will submit their Parameter Study towards the end of the course.
- 100% online course
- Expert instructors
- Flexible deadlines
- Shareable e-certificate
- Practice quizzes
- English subtitles
- Graded feedback
- Intermediate level course
- Financial add
- Coursera plus
- Flexible deadlines
- Self-paced learning
- Graded programming assignments
- Peer feedback
- Practice quizzes
Course and certificate fees
- A Complete Reinforcement Learning System (Capstone) fees is Rs. 5792 per month
- Initially, the programme is available to try free for 7 days.
Fees (per month)
After 7 days of trials
certificate providing authority
Who it is for
The Reinforcement Learning System (Capstone) programme by Coursera is recommended for professionals who have studied computer science at the undergraduate level, for at least one year. Or else, candidates who want to pursue a career in Artificial Intelligence and Data Science.
This course is a part of the Reinforcement Learning Specialisation programme offered by Coursera. Thus, candidates who want to enrol for the Reinforcement Learning System (Capstone) by Coursera should have completed the first three courses in this specialisation programme.
Furthermore, you need intermediate-level knowledge of introductory linear algebra, Python 3.0 (at least one year), calculus, and probability. You should also know how to implement algorithms using pseudocode.
What you will learn
After successful completion of the Complete Reinforcement Learning System (Capstone) programme, candidates will have gained knowledge of the following:
- Skills such as Artificial Intelligence, Machine Learning and Reinforcement Learning
- How to understand a problem, create a skeleton code for it and fully translate it to MDP
- Different algorithms and how to assess the appropriateness of each one for a given problem
- How to implement your agent using Neural Network
To enrol for the Reinforcement Learning System (Capstone) certification course by Coursera, candidates need to follow the steps given below:
- Visit the course page.
- You will find the ‘Enroll for Free’ option under the course title on the page.
- Select the option and fill in your payment details. You will get a 7-day free trial, after which you can cancel the subscription before the money is deducted.
- Alternatively, you can choose the Audit option and audit the course for free.
Filling the form
Candidates do not need to fill a separate application for the Reinforcement Learning System (Capstone) programme. You can simply enrol for the course by logging in to your existing Coursera account or creating a new one. After this, you have to select your preferred mode of payment and complete the fee payment for a successful application.
Welcome to the Final Capstone Course
Formalise Word Problem as MDP
- Formalising the problem
- Markov decision processes
- Eligibility traces and why they are named so
- Examples of continuing and episodic tasks
Choosing the Right Algorithm
- Choosing the learning algorithm
- What is Q-learning
- Actor-critic algorithm
- Expected sarsa
- Average reward: a new technique for formulating control problems
- Problem landscape
- Advice for students
Identify Key Performance Parameters
- Overview of design choices
- System ID + optimal control
- Approximation in Neural Networks
- RL in mobile health
Implement Your Agent
- Getting the agent details right
- Expected sarsa with function approximation
- In-depth on experience replay
- Optimisation strategies for NNs
- Dyna and Q-learning in a simple maze
- The framework ‘Collect and Infer’ for data-efficient RL
Submit Your Parameter Study
- Parameter studies in RL
- RL that matters
- Comparing TD and Monte Carlo
- Discussing your results
- Course wrap-up
- Specialisation wrap-up
Candidates who face difficulty in paying the course fees can avail of Coursera’s financial aid for the Reinforcement Learning System (Capstone) online course. For this, candidates need to fill an application form by clicking on the ‘Financial Aid’ option available at the top of the page.
These applications take around 15 days to get reviewed. Coursera will notify you regarding the application approval via email.
How it helps
Reinforcement Learning is an adaptive learning system that allows you to solve real-world problems. After taking the Reinforcement Learning System (Capstone) course and completing the other specialization courses in Reinforcement learning – candidates will be able to apply the skills acquired in game development (AI), industrial control, customer interaction and much more.
Moreover, candidates will also gain skills like AI, Python, Intelligent Systems, and Function Approximation, which will enable them to opt for more advanced courses as well.
Yes, there is an option to audit the course for free. However, in this option, you do not get practice assignments or a certificate.
Yes, the University of Alberta’s Alberta Machine Intelligence Institute offers the Reinforcement Learning System (Capstone) course. This is a world-renowned Alberta-based research institute in Machine Intelligence.
Since the Reinforcement Learning System (Capstone) online course falls under the domain of data science, there is intensive practical learning. Candidates need to apply empirical learnings, submit projects, and perform graded tests and assignments. You also get a practice exercise to consolidate your knowledge.
Coursera is the leading online certification provider where you can get unlimited professional certificates and learn anything. You can also get a Courser Plus membership which gives you unlimited access to guided projects and specializations.
The certificate displays the name of the candidate and indicates the successful completion of the course by the candidate. This certificate can be shared on your LinkedIn profile, printed resumes, and CVs.
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