Study reinforcement learning from fundamentals to advanced techniques including Q-learning, policy gradients, and multi-agent systems.
Learn University of AlbertaFundamentals of Reinforcement LearningCourse
DeepMind and UCL course on Deep Reinforcement Learning. Learn the fundamentals of RL and deep RL from researchers at DeepMind.
Learn DeepLearning.AIUnsupervised Learning, Recommenders, Reinforcement LearningCourse
Master RL algorithms from Q-learning to PPO. Build agents that learn from interaction and make optimal decisions.
Comprehensive course on Reinforcement Learning on AWS taught by AWS. Part of AWS ML curriculum.
Learn Reinforcement Learning: Complete Course with Python
Are you short on time to start from scratch to use deep learning to solve complex problems involving topics like neural networks and reinforcement learning? Than this course is for you!This course is designed to help you to overcome various data science problems by using efficient deep learning models built in TensorFlow. You will begin with a quick introduction to TensorFlow essentials. Next, you start with deep neural networks for different problems and also explore the applications of Convolutional Neural Networks on two real datasets. We will than walk you through different approaches to RL. You’ll move from a simple Q-learning to a more complex, deep RL architecture and implement your algorithms using Tensorflow’s Python API. You’ll be training your agents on two different games in a number of complex scenarios to make them more intelligent and perceptive.By the end of this course, you’ll be able to implement RL-based solutions in your projects from scratch using Tensorflow and Python. Also you will be able to develop deep learning based solutions to any kind of problem you have, without any need to learn deep learning models from scratch, rather using tensorflow and it’s enormous power.Contents and OverviewThis training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.The first course, Hands-on Deep Learning with TensorFlow is designed to help you to overcome various data science problems by using efficient deep learning models built in TensorFlow.The course begins with a quick introduction to TensorFlow essentials. Next, we start with deep neural networks for different problems and then explore the applications of Convolutional Neural Networks on two real datasets. If you’re facing time series problem then we will show you how to tackle it using RNN. We will also highlight how autoencoders can be used for efficient data representation. Lastly, we will take you through some of th
This course teaches the fundamentals and principal AI concepts about clustering, dimensionality reduction, reinforcement learning, and deep learning to solve real-life problems. Students will learn the basics of several machine learning topics to help solve real-life challenges, including unsupervised learning techniques such as clustering and dimensionality reduction.
This course covers the fundamentals of unsupervised learning techniques such as clustering and dimensionality reduction to make sense of large, unlabeled datasets. You will learn to implement k-means and hierarchical clustering.
Lead the GenAI revolution with this CrewAI course. Build and manage AI agents capable of intricate workflows, leverage agentic workflows, integrate LLMs, and future-proof your skills in AI automation.
This course introduces the fundamentals of reinforcement learning, guiding learners on how to frame RL problems and tackle classic examples. It covers basic algorithms and progresses to using function approximation with deep learning. It also features 'Project Malmo' for AI experimentation within Minecraft.
In partnership with AMD, this course teaches how to apply fine-tuning and reinforcement learning to improve LLM behavior, reasoning, and safety. You will learn about the post-training lifecycle, core techniques like RLHF and LoRA, and how to design evaluations to detect issues like reward hacking and diagnose failures.
This course will cover the fundamentals of deep reinforcement learning, one of the most exciting areas of machine learning today.
Learn Reinforcement Learning Specialization
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