Multi-Armed Bandits Courses and Certifications

Pascal Poupart

CS885: Multi-Armed Bandits

Explore the exploration–exploitation tradeoff in stochastic multi-armed bandits, from gambling models and regret to epsilon-greedy strategies and practical online optimization.

• YouTube
• 57 minutes
• Self-Paced
• Free Video

University of Alberta;  Alberta Machine Intelligence Institute

Fundamentals of Reinforcement Learning

25 ratings

Reinforcement Learning is a subfield of Machine Learning, but is also a general purpose formalism for automated decision-making and AI. This course introduces you to statistical learning techniques where an agent explicitly takes actions and interacts wi…

• Coursera
• 5 weeks, 3 hours a week
• Self-Paced
• Paid Course

• Best of All Time

MLOps World: Machine Learning in Production

Multi-armed Bandits in Production at Stitch Fix

Explore scaling challenges and solutions for multi-armed bandits in online experimentation, including a new method for efficient, deterministic Thompson sampling at Stitch Fix.

• YouTube
• 40 minutes
• Self-Paced
• Free Video

VinAI

Adversarially Robust Stochastic Multi-Armed Bandits

Explore adversarially robust stochastic multi-armed bandits for optimal experimental design. Learn about algorithms balancing fast and robust learning in real-world applications like digital advertising.

• YouTube
• 45 minutes
• Self-Paced
• Free Video

IIT Bombay;  NPTEL

Bandit Algorithm (Online Machine Learning)

Study bandit algorithms for balancing exploration and exploitation in stochastic and adversarial online learning settings.

• Swayam
• 12 weeks
• Available until Oct 9, 2026
• Free Online Course

Pascal Poupart

Bayesian and Contextual Bandits

Learn Bayesian and contextual bandits through Beta distributions, belief updates, Thompson sampling, Bernoulli rewards, and approximate reward functions.

• YouTube
• 1 hour 17 minutes
• Self-Paced
• Free Video

EDGE AI FOUNDATION

Multi-armed Bandit on System-on-Chip - Go Frequentist or Bayesian?

Explore multi-armed bandit algorithms for edge computing, focusing on UCB, KLUCB, and Thompson Sampling implementations on System-on-Chip for IoT, wireless radio, and robotics applications.

• YouTube
• 1 hour 8 minutes
• Self-Paced
• Free Video

Dave Churchill

Introduction to Artificial Intelligence - Bandit Algorithms - Lecture 16

Explore bandit algorithms in artificial intelligence, learning key techniques for modern problem-solving environments and their application in game development.

• YouTube
• 1 hour 1 minute
• Self-Paced
• Free Video

Artificial Intelligence: Reinforcement Learning in Python

10817 ratings at Udemy

Complete guide to Reinforcement Learning, with Stock Trading and Online Advertising Applications

• Udemy
• 14 hours 43 minutes
• Self-Paced
• Paid Course

Decision Making and Reinforcement Learning

25 ratings at Coursera

Model sequential decisions and implement RL algorithms: multi-armed bandits, MDPs and POMDPs, value and policy iteration, Monte Carlo control, SARSA, Q-learning and n-step TD.

• Coursera
• 8 weeks, 6 hours a week
• Self-Paced
• Paid Course

Mastering Classic Reinforcement Learning Algorithms

Formulate decisions as finite Markov decision processes and solve them with value iteration, policy iteration, bandits, Monte Carlo methods, temporal-difference learning, SARSA, and Q-learning.

• Coursera
• 5 weeks, 3 hours a week
• Self-Paced
• Paid Course

Build Python agents in Gymnasium that learn through trial and error, applying rewards, policies, Q-learning, SARSA, bandits, and Markov Decision Processes.

• Codecademy
• 2 hours
• Self-Paced
• Free Trial Available

Reinforcement Learning

Learn reinforcement learning from the basics: bandit algorithms (UCB, PAC, median elimination), Markov decision processes, dynamic programming, temporal difference methods, Bellman equations, policy gradients, and deep Q-learning.

• Edureka
• Self-Paced
• Paid Course

Pascal Poupart

Reinforcement Learning - Spring 2018

Master reinforcement learning algorithms that enable machines to learn from partial feedback, covering Markov processes, deep RL, bandits, and applications in robotics and games.

• YouTube
• 1 day 22 minutes
• Self-Paced
• Free Video

CodeEmporium

Reinforcement Learning 101

Discover the fundamentals of reinforcement learning through multi-armed bandits, Q-learning, deep Q-networks, and policy optimization techniques used in modern AI systems.

• YouTube
• 2 hours 4 minutes
• Self-Paced
• Free Video