Reinforcement Learning
Access Duration - 365 Days
4.5( 2 REVIEWS )
139 STUDENTS
What Will I Learn?
Learn to build a Reinforcement Learning system
Learn how to formalise tasks as a Reinforcement Learning problem
Learn how RL complements deep learning
Learn how to make decisions in uncertain environments
Learn about Policy Gradient methods
Overview
Reinforcement Learning is designed for learners to learn from the outcome of your own decision. It is a part of machine learning and will help solve a certain type of problem where it is sequential decision-making and it’s long-term. Learners will be introduced to the fundamentals of Reinforcement Learning and OpenAI Gym. There are key modules fully explored in this course including Bandit algorithms, Markov Decision Processes, Temporal Difference Methods and Dynamic Programming. In an uncertain environment, you will learn to make effective decisions.
Reinforcement Learning will provide a wealth of knowledge on efficient algorithms, single-agent planning and multi-agent planning. The course will ensure topics are discussed at length in order for learners to gain a complete understanding of the subject at hand.
Reinforcement Learning will set you in the right direction, giving you the opportunity to open the door to new and exciting job roles in machine learning and artificial intelligence.
Why You Should Consider Taking this Course at Global Edulink?
Global Edulink is a leading online provider for several accrediting bodies, and provides learners the opportunity to take this exclusive course awarded by CPD. At Global Edulink, we give our fullest attention to our learners’ needs and ensure they have the necessary information required to proceed with the Course. Learners who register will be given excellent support, discounts for future purchases and be eligible for a TOTUM Discount card and Student ID card with amazing offers and access to retail stores, the library, cinemas, gym memberships and their favourite restaurants.
- Access Duration
- Who is this Course for?
- Entry Requirement
- Method of Assessment
- Certification
- Awarding Body
- Career Path & Progression
The course will be directly delivered to you, and you have 12 months access to the online learning platform from the date you joined the course. The course is self-paced and you can complete it in stages, revisiting the lessons at any time.
This course is recommended for,
- Web Developers
- Software Developers
- Programmers
- Learners should be over the age of 16, and have a basic understanding of English, ICT and numeracy.
- A sound educational background is recommended
- Knowledge of Python essentials is recommended
- Understanding of statistics and machine learning algorithms
In order to qualify in the course ‘Reinforcement Learning’ successfully, learners will take an online test with each module being rounded off with multiple-choice questions. This online test is marked automatically, so you will receive an instant grade and know whether you have passed the course.
Upon the successful completion of the course, you will be awarded the Certificate in Reinforcement Learning by CPD.
CPD is a leading awarding body in the United Kingdom that meets an excellent standard of high quality education. CPD is committed towards the enhancement of proficiency and personal skills in order to develop learners’ skills and abilities. CPD ensures that both practical and academic qualifications assist individuals to re-skill or up-skill and maintain a competitive advantage in their chosen industry.
Reinforcement Learning will improve your candidature for a number of jobs in machine learning and development. You can study further courses in the same field and enhance your academic expertise in artificial intelligence and machine learning, and add this as a valuable skillset on your resume. Your skills will be recognised by leading organisations that give you the opportunity to land a well-paying job. Given below are job titles you can compete for, along with the average UK salary per annum according to https://www.glassdoor.com.
- Web Developers - £50,000 (Approximately)
- Software Developers - £70,000 (Approximately)
- Programmers - £50,000 (Approximately)
Key Features
Gain an Accredited UK Qualification
Access to Excellent Quality Study Materials
Personalised Learning Experience
Support by Phone, Live Chat, and Email
Eligible for TOTUM Discount Card
UK Register of Learning Providers Reg No : 10053842Course Curriculum
| 1: Introduction to Reinforcement Learning | |||
| 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 | |||
| 2: Bandit Algorithms and Markov Decision Process | |||
| Bandit Algorithms | |||
| Markov Process | |||
| Markov Reward Process | |||
| Markov Decision Process | |||
| 3: Dynamic Programming & Temporal Difference Methods | |||
| Introduction to Dynamic Programming | |||
| Dynamic Programming Algorithms | |||
| Monte Carlo Methods | |||
| Temporal Difference Learning Methods | |||
| 4: Deep Q Learning | |||
| Policy Gradients | |||
| Policy Gradients using TensorFlow | |||
| Deep Q learning | |||
| Q learning with replay buffers, target networks, and CNN | |||
| 5: In-class Project | |||
Alex Rees
The course introduced me to Reinforcement Learning, and as a web developer, I gained a wealth of knowledge on Markov Decision Processes and Dynamic Programming.
Gale Clark
The support I received from the provider was truly fantastic. They were helpful to me every step if the way.