Reinforcement Learning

Reinforcement Learning is a type of Machine Learning where an agent learns to make decisions by taking actions in an environment to maximize a reward. Coursera's Reinforcement Learning catalogue teaches you the foundational principles and algorithms of reinforcement learning. You'll understand the exploration-exploitation tradeoff, learn about Markov Decision Processes (MDPs), and explore different methods for value function approximation. You'll also learn how to implement various reinforcement learning algorithms such as Q-Learning, Policy Gradient methods, and Deep Q-Networks (DQN). The understanding gained from these courses will equip you to handle complex real-world problems like game playing, robotics, navigation, and more.
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Explore the Reinforcement Learning Course Catalog

  • Status: Free Trial

    University of Alberta

    Skills you'll gain: Reinforcement Learning, Machine Learning, Sampling (Statistics), Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Machine Learning Algorithms, Deep Learning, Simulations, Feature Engineering, Markov Model, Supervised Learning, Algorithms, Artificial Neural Networks, Performance Testing, Linear Algebra, Performance Tuning, Pseudocode, Probability Distribution

  • Status: Free Trial

    Skills you'll gain: Reinforcement Learning, Machine Learning, Artificial Intelligence, Markov Model, Algorithms, Linear Algebra, Probability Distribution

  • Status: New
    Status: Preview

    Skills you'll gain: Reinforcement Learning, Dimensionality Reduction, PyTorch (Machine Learning Library), Deep Learning, Generative AI, Pandas (Python Package), Scikit Learn (Machine Learning Library), Python Programming, Machine Learning, Artificial Neural Networks, Data Processing, Natural Language Processing, Feature Engineering, Predictive Modeling, Supervised Learning, Unsupervised Learning, Data Transformation, NumPy

  • Status: Free Trial

    Skills you'll gain: Unsupervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Data Ethics, Machine Learning, Supervised Learning, Artificial Intelligence, Reinforcement Learning, Deep Learning, Anomaly Detection, Dimensionality Reduction, Algorithms

  • Status: Preview

    Skills you'll gain: Reinforcement Learning, Game Theory, Artificial Intelligence and Machine Learning (AI/ML), Operations Research, Machine Learning, Markov Model, Deep Learning, Algorithms, Decision Support Systems, Simulations, Mathematical Modeling, Probability, Statistical Methods

  • Status: Free Trial

    Skills you'll gain: Reinforcement Learning, Generative Model Architectures, Deep Learning, Unsupervised Learning, Image Analysis, Artificial Neural Networks, Keras (Neural Network Library), Machine Learning Algorithms, Machine Learning, Artificial Intelligence, Computer Vision, Applied Machine Learning, Dimensionality Reduction, Natural Language Processing

What brings you to Coursera today?

  • Status: Free Trial

    Multiple educators

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Classification And Regression Tree (CART), Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Machine Learning, Jupyter, Data Ethics, Decision Tree Learning, Tensorflow, Responsible AI, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Reinforcement Learning, Random Forest Algorithm, Feature Engineering, Python Programming

  • Status: Free

    Skills you'll gain: LLM Application, Large Language Modeling, Prompt Engineering, Reinforcement Learning, Machine Learning Methods

  • Status: New
    Status: Preview

    Skills you'll gain: Reinforcement Learning, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Applied Machine Learning, Machine Learning, Control Systems, Simulations

  • Status: Free Trial

    Multiple educators

    Skills you'll gain: Tensorflow, Keras (Neural Network Library), Machine Learning, Google Cloud Platform, Machine Learning Algorithms, Applied Machine Learning, Financial Trading, Reinforcement Learning, Supervised Learning, Data Pipelines, Time Series Analysis and Forecasting, Statistical Machine Learning, Technical Analysis, Deep Learning, Securities Trading, Portfolio Management, Market Trend, Artificial Intelligence and Machine Learning (AI/ML), Financial Market, Artificial Neural Networks

  • Status: Free Trial

    Skills you'll gain: Supervised Learning, Reinforcement Learning, Applied Machine Learning, Machine Learning, Statistical Methods, Dimensionality Reduction, Unsupervised Learning, Artificial Neural Networks, Decision Tree Learning, Predictive Modeling, Financial Trading, Financial Market, Derivatives, Scikit Learn (Machine Learning Library), Markov Model, Regression Analysis, Market Dynamics, Risk Modeling, Tensorflow, Financial Modeling

  • Status: Free Trial

    Johns Hopkins University

    Skills you'll gain: PyTorch (Machine Learning Library), Unsupervised Learning, Computer Vision, Machine Learning Algorithms, Applied Machine Learning, Image Analysis, Dimensionality Reduction, Supervised Learning, Reinforcement Learning, Feature Engineering, Regression Analysis, Data Cleansing, Machine Learning, Data Mining, Scikit Learn (Machine Learning Library), Statistical Machine Learning, Advanced Analytics, Deep Learning, Artificial Neural Networks, Decision Tree Learning

What brings you to Coursera today?

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  • IBM
  • Johns Hopkins University
  • Alberta Machine Intelligence Institute
  • Google Cloud
  • New York University
  • Simplilearn
  • University of Alberta
  • DeepLearning.AI