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

    Skills you'll gain: Reinforcement Learning, Applied Machine Learning, Machine Learning Algorithms, Artificial Intelligence, Dimensionality Reduction, Statistical Analysis, Classification And Regression Tree (CART), Supervised Learning, Unsupervised Learning, Predictive Modeling, Random Forest Algorithm, Feature Engineering, Data Manipulation

  • Status: Preview

    University of Washington

    Skills you'll gain: Organizational Skills, Process Design, Artificial Intelligence, Functional Design, Goal Setting, Verification And Validation, Reinforcement Learning, Functional Specification, Knowledge Transfer, Design Strategies, Software Architecture, Software Design Patterns, Decision Making

  • Status: Free Trial

    Skills you'll gain: Reinforcement Learning, Google Cloud Platform, AI Personalization, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Machine Learning Algorithms, Deep Learning, Applied Machine Learning, Artificial Neural Networks, Predictive Modeling, Algorithms, Data Processing

  • Status: Free Trial

    Politecnico di Milano

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Machine Learning Algorithms, Machine Learning, Reinforcement Learning, Dimensionality Reduction, Algorithms, Data Mining, Classification And Regression Tree (CART), Regression Analysis

  • Status: Preview

    Skills you'll gain: Reinforcement Learning, Deep Learning, Theoretical Computer Science, Artificial Neural Networks, Artificial Intelligence, Machine Learning, Computational Logic, Supervised Learning, Computer Science, Decision Tree Learning, Unsupervised Learning, Algorithms

  • Status: Free Trial

    Skills you'll gain: Reinforcement Learning, Data-Driven Decision-Making, Markov Model, Time Series Analysis and Forecasting, Bayesian Statistics, Data Science, Predictive Analytics, Anomaly Detection, Probability Distribution, Machine Learning Methods, Statistical Analysis, A/B Testing, Sampling (Statistics)

  • Status: Free Trial

    Skills you'll gain: Game Theory, Data-Driven Decision-Making, Cybersecurity, Data Science, Algorithms, Reinforcement Learning, Machine Learning Algorithms, Applied Machine Learning, Machine Learning

  • Status: Free Trial

    University of Colorado System

    Skills you'll gain: Marketing Analytics, Anomaly Detection, Advanced Analytics, Bayesian Network, Data-Driven Decision-Making, Marketing Effectiveness, Forecasting, Marketing Strategies, Strategic Decision-Making, Strategic Leadership, Time Series Analysis and Forecasting, Simulation and Simulation Software, Predictive Analytics, Customer Analysis, Customer Engagement, Bayesian Statistics, Customer Retention, Consumer Behaviour, Reinforcement Learning, Probability Distribution

  • Status: Preview

    Skills you'll gain: Deep Learning, Artificial Neural Networks, Computer Vision, Machine Learning Methods, Generative AI, Natural Language Processing, Scalability, Reinforcement Learning, Network Architecture, Performance Tuning

  • Skills you'll gain: Social Network Analysis, Systems Thinking, Reinforcement Learning, Data Storytelling, Unsupervised Learning, Computer Vision, Deep Learning, Time Series Analysis and Forecasting, Predictive Modeling, Project Management Life Cycle, Statistical Analysis, Financial Data, Marketing Analytics, MLOps (Machine Learning Operations), Strategic Decision-Making, Descriptive Analytics, Simulations, Random Forest Algorithm, Operations Research, Stakeholder Engagement

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