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    • Reinforcement Learning

    Reinforcement Learning Courses Online

    Study reinforcement learning for AI applications. Learn to design algorithms that learn from interaction with their environment.

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    Explore the Reinforcement Learning Course Catalog

    • D

      Duke University

      MLOps | Machine Learning Operations

      Skills you'll gain: MLOps (Machine Learning Operations), Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Data Ethics, Application Deployment, Data Manipulation, Exploratory Data Analysis, Containerization, Data Pipelines, CI/CD, Software Testing, Data Import/Export, Amazon Web Services, Feature Engineering, Cloud Solutions, Artificial Intelligence and Machine Learning (AI/ML), Docker (Software), Rust (Programming Language)

      4.2
      Rating, 4.2 out of 5 stars
      ·
      449 reviews

      Advanced · Specialization · 3 - 6 Months

    • G

      Google

      Google IT Automation with Python

      Skills you'll gain: Git (Version Control System), GitHub, Version Control, Cloud Services, Debugging, Puppet (Configuration Management Tool), Infrastructure as Code (IaC), Bash (Scripting Language), Configuration Management, CI/CD, Cloud Computing, Technical Communication, Docker (Software), Unit Testing, Scripting, Network Troubleshooting, Web Services, Python Programming, Restful API, Programming Principles

      4.7
      Rating, 4.7 out of 5 stars
      ·
      48K reviews

      Advanced · Professional Certificate · 3 - 6 Months

    • I

      IBM

      IBM AI Developer

      Skills you'll gain: Generative AI, Prompt Engineering, Large Language Modeling, Software Development Life Cycle, Unit Testing, ChatGPT, HTML and CSS, Development Environment, Web Design and Development, Jupyter, Hypertext Markup Language (HTML), Software Engineering, Artificial Intelligence, Cascading Style Sheets (CSS), Software Development Tools, Web Development, Application Deployment, Automation, Interviewing Skills, Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      68K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      IBM

      Deep Learning with PyTorch

      Skills you'll gain: PyTorch (Machine Learning Library), Deep Learning, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Computer Vision, Applied Machine Learning, Supervised Learning, Regression Analysis

      4.4
      Rating, 4.4 out of 5 stars
      ·
      41 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      Y

      Yale University

      Introduction to Psychology

      Skills you'll gain: Psychology, Mental and Behavioral Health Specialties, Child Development, Mental Health, Human Learning, Social Sciences, Behavioral Health, Neurology, Biology, Scientific Methods

      4.9
      Rating, 4.9 out of 5 stars
      ·
      31K reviews

      Beginner · Course · 1 - 3 Months

    • G

      Google Cloud

      Advanced Machine Learning on Google Cloud

      Skills you'll gain: Natural Language Processing, MLOps (Machine Learning Operations), Tensorflow, Large Language Modeling, Reinforcement Learning, Computer Vision, Google Cloud Platform, Keras (Neural Network Library), Systems Design, Image Analysis, Hybrid Cloud Computing, Applied Machine Learning, Systems Architecture, Performance Tuning, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Artificial Neural Networks, Machine Learning, Machine Learning Algorithms, Distributed Computing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      1.5K reviews

      Advanced · Specialization · 3 - 6 Months

    • G

      Google Cloud

      Introduction to Generative AI Learning Path

      Skills you'll gain: Large Language Modeling, Generative AI, Prompt Engineering, Data Ethics, Google Cloud Platform, Business Ethics, Application Development, Artificial Intelligence, Accountability, Regulatory Compliance, Compliance Training, Ethical Standards And Conduct, Data Governance, Artificial Intelligence and Machine Learning (AI/ML), Governance, Organizational Effectiveness, Machine Learning, Machine Learning Methods, Decision Making

      4.6
      Rating, 4.6 out of 5 stars
      ·
      8.8K reviews

      Intermediate · Specialization · 1 - 3 Months

    • N

      New York University

      Overview of Advanced Methods of Reinforcement Learning in Finance

      Skills you'll gain: Reinforcement Learning, Financial Trading, Financial Market, Derivatives, Market Liquidity, Finance, Market Dynamics, Financial Modeling, Securities (Finance), Artificial Intelligence and Machine Learning (AI/ML), Credit Risk, Machine Learning, Physics

      3.8
      Rating, 3.8 out of 5 stars
      ·
      84 reviews

      Advanced · Course · 1 - 4 Weeks

    • Status: Free
      Free
      E

      Edge Impulse

      Introduction to Embedded Machine Learning

      Skills you'll gain: Applied Machine Learning, Embedded Systems, Data Processing, Machine Learning, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Data Ethics, Deep Learning, Feature Engineering, Performance Tuning

      4.8
      Rating, 4.8 out of 5 stars
      ·
      719 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free
      M

      McMaster University

      Mindshift: Break Through Obstacles to Learning and Discover Your Hidden Potential

      Skills you'll gain: Lifelong Learning, Willingness To Learn, Learning Strategies, Growth Mindedness, Mentorship, Adaptability, Professional Development, Personal Development, Productivity, Open Mindset, Resilience, Stress Management, Overcoming Obstacles, Curiosity, Cognitive flexibility

      4.8
      Rating, 4.8 out of 5 stars
      ·
      13K reviews

      Beginner · Course · 1 - 4 Weeks

    • D

      Duke University

      Introduction to Machine Learning

      Skills you'll gain: PyTorch (Machine Learning Library), Reinforcement Learning, Image Analysis, Applied Machine Learning, Deep Learning, Machine Learning, Natural Language Processing, Supervised Learning, Unsupervised Learning, Artificial Neural Networks, Computer Vision, Medical Imaging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.7K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      D

      Deep Teaching Solutions

      Learning How to Learn: Powerful mental tools to help you master tough subjects

      Skills you'll gain: Learning Strategies, Time Management, Human Learning, Willingness To Learn, Productivity, Growth Mindedness, Mental Concentration, Creativity, Problem Solving, Self-Discipline, Cognitive flexibility, Stress Management

      4.8
      Rating, 4.8 out of 5 stars
      ·
      92K reviews

      Beginner · Course · 1 - 4 Weeks

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    In summary, here are 10 of our most popular reinforcement learning courses

    • MLOps | Machine Learning Operations: Duke University
    • Google IT Automation with Python: Google
    • IBM AI Developer: IBM
    • Deep Learning with PyTorch: IBM
    • Introduction to Psychology : Yale University
    • Advanced Machine Learning on Google Cloud: Google Cloud
    • Introduction to Generative AI Learning Path: Google Cloud
    • Overview of Advanced Methods of Reinforcement Learning in Finance: New York University
    • Introduction to Embedded Machine Learning: Edge Impulse
    • Mindshift: Break Through Obstacles to Learning and Discover Your Hidden Potential: McMaster University

    Skills you can learn in Machine Learning

    Python Programming (33)
    Tensorflow (32)
    Deep Learning (30)
    Artificial Neural Network (24)
    Big Data (18)
    Statistical Classification (17)
    Reinforcement Learning (13)
    Algebra (10)
    Bayesian (10)
    Linear Algebra (10)
    Linear Regression (9)
    Numpy (9)

    Frequently Asked Questions about Reinforcement Learning

    Reinforcement learning is a machine learning paradigm in which software agents use a process of trial and error to learn how to complete tasks in a way that maximizes cumulative rewards as defined by their programmers. In contrast to supervised learning paradigms, reinforcement learning systems do not need labeled input/output pairs or explicit corrections of suboptimal actions; and, in contrast to unsupervised learning, reinforcement learning defines an explicit goal, which is the maximization of the value returned by the Q-learning (or “quality” learning) algorithm as a result of its actions.

    Because it combines the goal orientation of supervised learning with the flexibility of unsupervised learning, reinforcement learning is very important in creating artificial intelligence (AI) applications requiring successful problem-solving in complex situations. For example, they are often used in financial engineering to develop optimal trading algorithms for the stock market. They are also used to build intelligent systems to allow robots and self-driving cars to navigate real-world environments safely.‎

    As one of the main paradigms for machine learning, reinforcement learning is an essential skill for careers in this fast-growing field. Reinforcement learning is particularly important for developing artificially intelligent digital agents for real-world problem-solving in industries like finance, automotive, robotics, logistics, and smart assistants. According to Glassdoor, the average annual salary for machine learning engineers in America is $114,121 per year, a high level of pay which reflects the high level of demand for this expertise.‎

    Absolutely. Coursera hosts a wide variety of courses in reinforcement learning and related topics in machine learning, as well as the use of these techniques in applied contexts such as finance and self-driving cars. These courses and Specializations are offered by top-ranked institutions in this field, including the deepmind.ai, New York University, the University of Toronto, and the University of Alberta’s Machine Intelligence Institute. You can learn remotely on a flexible schedule while still getting feedback from expert professors and instructors, ensuring that you’ll get a high quality education with all the reinforcement you need to learn these valuable skills with confidence.‎

    Because reinforcement learning itself isn't a beginner-level subject, you'll need to have a good grasp on the fundamentals of machine learning before starting to learn it. Additionally, many courses will require you to have a strong background in high-level mathematics such as linear algebra, statistics, and probability. Most courses will require you to be proficient in Python, although people familiar with other programming languages like C++, Matlab, and JavaScript can often use those skills to help them learn reinforcement learning. Having the ability to implement algorithms from pseudocode may be another prerequisite. As you progress, you'll gain skills in using reinforcement learning solutions to solve problems with probabilistic artificial intelligence, function approximation, and intelligent systems.‎

    People best suited to roles within the reinforcement learning realm should have a passion for machine learning with a drive for analytics and data and an interest in providing frontline support to solve real-world problems while leveraging innate creative problem-solving skills. Additionally, many companies like to see that candidates have strong communication skills and the ability to collaborate across disciplines and departments. There are a variety of roles associated with reinforcement learning, including analysts, engineers, and researchers. In late February 2021, there were more than 1,800 job listings for people proficient in reinforcement learning on LinkedIn.‎

    If you want to be a part of the future of machine learning, learning reinforcement learning may be a good move for you. This innovative machine learning technique creates an algorithm that learns through trial and error, leading to a combination of short- and long-term rewards such as the ability to define sequences to solve problems using a reward-based learning approach. It's useful across multiple industries, including the tech industry, business, advertising, finance, and e-commerce, all of which find reinforcement learning useful in part because of its ability to offer greater personalization. Ultimately, if you want to work within AI and machine learning, this could be a step to advancing your goals.‎

    Online Reinforcement Learning courses offer a convenient and flexible way to enhance your knowledge or learn new Reinforcement Learning skills. Choose from a wide range of Reinforcement Learning courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Reinforcement Learning, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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