Overview
The Reinforcement Learning Specialization consists of 4 courses exploring the power of adaptive learning systems and artificial intelligence (AI).
Harnessing the full potential of artificial intelligence requires adaptive learning systems. Learn how Reinforcement Learning (RL) solutions help solve real-world problems through trial-and-error interaction by implementing a complete RL solution from beginning to end.
By the end of this Concepts of Reinforcement Learning with this Reinforcement Learning Specialization offered by Coursera in partnership with University of Alberta, learners will understand the foundations of much of modern probabilistic artificial intelligence (AI) and be prepared to take more advanced courses or to apply AI tools and ideas to real-world problems. This content will focus on “small-scale” problems in order to understand the foundations of Reinforcement Learning, as taught by world-renowned experts at the University of Alberta, Faculty of Science.
The tools learned in this Specialization can be applied to game development (AI), customer interaction (how a website interacts with customers), smart assistants, recommender systems, supply chain, industrial control, finance, oil & gas pipelines, industrial control systems, and more.
Applied Learning Project
Through programming assignments and quizzes, students will:
- Build a Reinforcement Learning system that knows how to make automated decisions.
- Understand how RL relates to and fits under the broader umbrella of machine learning, deep learning, supervised and unsupervised learning.
- Understand the space of RL algorithms (Temporal- Difference learning, Monte Carlo, Sarsa, Q-learning, Policy Gradient, Dyna, and more).
- Understand how to formalize your task as a RL problem, and how to begin implementing a solution.
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Visit programme websiteProgramme Structure
Courses included:
- Reinforcement Learning
- Sample-based Learning Methods
- Prediction and Control with Function Approximation
- A Complete Reinforcement Learning System (Capstone)
Check out the full curriculum
Visit programme websiteKey information
Duration
- Part-time
- 2 months
- 10 hrs/week
Start dates & application deadlines
Language
Delivered
Disciplines
Artificial Intelligence Machine Learning View 144 other Short Courses in Artificial Intelligence in United StatesExplore more key information
Visit programme websiteAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
Intermediate Level
- Probabilities & Expectations, basic linear algebra, basic calculus, Python 3.0 (at least 1 year), implementing algorithms from pseudocode
Make sure you meet all requirements
Visit programme websiteTuition Fee
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International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 2 months. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 2 months.
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Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.