Introduction to Learning

External: Coursera Courses ↗ · Coursera

Open Course on External: Coursera

Free to audit · Opens on External: Coursera

Introduction to Learning

Coursera · Beginner ·🎮 Reinforcement Learning ·4d ago

Key Takeaways

Introduction to supervised, unsupervised, and reinforcement learning using algorithms like decision trees and Q-learning

Original Description

This course introduces the foundational concepts of learning, focusing on supervised, unsupervised, and reinforcement learning. Students will learn how machines can learn from data to make predictions, find patterns, and make decisions over time. Topics include key algorithms such as decision trees, linear classifiers, clustering, and Q-learning. Students will develop a practical understanding of how learning systems work and how to apply them to real-world problems.
Watch on External: Coursera ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related AI Lessons

Proximal Policy Optimisation — The Clip That Made Policy Gradients Reliable
Learn how Proximal Policy Optimisation (PPO) makes policy gradients reliable in reinforcement learning
Medium · Machine Learning
Deep Q-Networks — When the Q-Table Won’t Fit
Learn to implement Deep Q-Networks in Python for reinforcement learning problems where the Q-table won't fit, and understand their benefits over traditional Q-learning
Medium · Python
Reward hacking in Reinforcement learning
Learn to identify and fix reward hacking in Reinforcement Learning, a crucial step in ensuring reliable AI decision-making
Medium · LLM
Learning by messing up: A beginner’s tour of Reinforcement Learning
Learn the basics of Reinforcement Learning, from agents and rewards to the Markov property and Gym environments, and start building your own RL projects
Medium · Deep Learning
Up next
Middle Management Meritocracy: Shockingly Naive
iBankerU
Watch →