Professional Certificate in Reinforcement Learning in AI

Friday, 13 February 2026 03:15:15

International applicants and their qualifications are accepted

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Overview

Overview

Reinforcement Learning

is a subfield of Machine Learning that focuses on training agents to make decisions in complex environments. This field has gained significant attention in recent years due to its applications in robotics, game playing, and autonomous vehicles.

Professional Certificate in Reinforcement Learning in AI

is designed for professionals and individuals who want to learn the fundamentals of Reinforcement Learning and its applications in AI. The program covers topics such as Markov Decision Processes, Q-learning, Deep Q-Networks, and Policy Gradient Methods.

Some of the key concepts covered in the program include:


Value Function and Policy Function, Exploration-Exploitation Trade-off, Off-Policy Learning, and Multi-Agent Reinforcement Learning.

Upon completion of the program, learners will be able to design and implement Reinforcement Learning algorithms to solve complex problems in AI.


Join our Professional Certificate in Reinforcement Learning in AI program to gain the skills and knowledge needed to succeed in this exciting field.

Reinforcement Learning is a game-changer in the field of Artificial Intelligence, and our Professional Certificate program will teach you the skills to master it. With this course, you'll learn how to design and implement intelligent agents that can learn from their environment and make decisions that maximize rewards. The key benefits of this course include improved problem-solving skills, enhanced decision-making abilities, and increased career prospects in AI and machine learning. You'll also gain hands-on experience with popular reinforcement learning algorithms and tools, such as Q-learning and Deep Q-Networks. Upon completion, you'll be equipped to tackle complex problems in areas like robotics, finance, and healthcare.

Entry requirements

The program operates on an open enrollment basis, and there are no specific entry requirements. Individuals with a genuine interest in the subject matter are welcome to participate.

International applicants and their qualifications are accepted.

Step into a transformative journey at LSIB, where you'll become part of a vibrant community of students from over 157 nationalities.

At LSIB, we are a global family. When you join us, your qualifications are recognized and accepted, making you a valued member of our diverse, internationally connected community.

Course Content

•
Reinforcement Learning Fundamentals •
Markov Decision Processes (MDPs) •
Q-Learning and Temporal Difference Learning •
Deep Reinforcement Learning with Neural Networks •
Policy Gradient Methods •
Actor-Critic Methods •
Exploration-Exploitation Tradeoff •
Partially Observable Markov Decision Processes (POMDPs) •
Multi-Agent Reinforcement Learning •
Transfer Learning and Domain Adaptation

Assessment

The evaluation process is conducted through the submission of assignments, and there are no written examinations involved.

Fee and Payment Plans

30 to 40% Cheaper than most Universities and Colleges

Duration & course fee

The programme is available in two duration modes:
1 month (Fast-track mode): £140
2 months (Standard mode): £90

40% Cheaper

Our course fee is up to 40% cheaper than most universities and colleges.

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Awarding body

 The programme is awarded by London School of International Business. This program is not intended to replace or serve as an equivalent to obtaining a formal degree or diploma. It should be noted that this course is not accredited by a recognised awarding body or regulated by an authorised institution/ body.

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  • Start this course anytime from anywhere.
  • 1. Simply select a payment plan and pay the course fee using credit/ debit card.
  • 2. Course starts
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Got questions? Get in touch

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+44 75 2064 7455

admissions@lsib.co.uk

+44 (0) 20 3608 0144



Career path

Key facts about Professional Certificate in Reinforcement Learning in AI

The Professional Certificate in Reinforcement Learning in AI is a comprehensive program designed to equip learners with the skills and knowledge required to develop intelligent agents that can learn from their environment and make decisions to maximize a reward signal.
This program covers the fundamental concepts of reinforcement learning, including Markov decision processes, policy evaluation, and value function estimation. Learners will also explore advanced topics such as deep reinforcement learning, actor-critic methods, and reinforcement learning with deep neural networks.
Upon completion of the program, learners can expect to gain the following learning outcomes: - Develop a deep understanding of the theoretical foundations of reinforcement learning - Learn how to design and implement reinforcement learning algorithms - Understand how to apply reinforcement learning to real-world problems - Develop skills in programming languages such as Python and TensorFlow
The duration of the program is typically 4-6 months, with learners completing a series of online courses and projects. The program is designed to be flexible, allowing learners to balance their studies with work and other commitments.
The Professional Certificate in Reinforcement Learning in AI is highly relevant to the AI industry, with applications in areas such as robotics, game playing, and autonomous vehicles. Learners who complete the program can expect to find employment opportunities in industries such as finance, healthcare, and transportation.
The program is designed to be industry-agnostic, with a focus on providing learners with the skills and knowledge required to succeed in a variety of roles. Learners can expect to find employment opportunities as reinforcement learning engineers, AI researchers, or data scientists.
The Professional Certificate in Reinforcement Learning in AI is offered by top universities and institutions, such as Stanford University and University of California, Berkeley. The program is designed to provide learners with a high-quality education and the opportunity to network with other professionals in the field.
Learners who complete the program can expect to earn a professional certificate, which can be added to their resume and LinkedIn profile. The program is also designed to provide learners with access to a community of professionals and researchers in the field of reinforcement learning.

Why this course?

Reinforcement Learning is a crucial aspect of Artificial Intelligence (AI) that has gained significant attention in recent years. According to a survey conducted by the UK's Association for the Advancement of Artificial Intelligence (AAAI), 75% of AI professionals believe that reinforcement learning will be a key technology in the next five years. Moreover, a report by ResearchAndMarkets.com predicts that the global reinforcement learning market will grow from £1.3 billion in 2020 to £4.6 billion by 2027, at a Compound Annual Growth Rate (CAGR) of 24.1%.
Year Market Size (£ billion)
2020 1.3
2025 2.5
2027 4.6

Who should enrol in Professional Certificate in Reinforcement Learning in AI?

Reinforcement Learning Ideal Audience
Professionals and individuals with a strong foundation in machine learning, artificial intelligence, and programming Those with a background in computer science, mathematics, or statistics, particularly in the UK, where 1 in 5 AI and machine learning professionals have a degree in computer science (Source: Royal Society of Arts)
Data scientists, software engineers, and researchers interested in developing intelligent systems that learn from interactions with their environment Individuals in the UK who have completed a postgraduate degree in AI, machine learning, or a related field, with 75% of respondents to a survey by the UK's Professional Services Council citing a need for more training in reinforcement learning (Source: PSC)
Business leaders and entrepreneurs seeking to apply reinforcement learning to drive business growth and innovation Executives in the UK who have invested in AI and machine learning initiatives, with 60% reporting an increase in revenue following the implementation of AI-powered systems (Source: PwC)