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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

    • Status: Free
      Free
      U

      University at Buffalo

      ADHD: Everyday Strategies for Elementary Students

      Skills you'll gain: Psychological Evaluations, Classroom Management, Teaching, Instructional Strategies, Student Engagement, Parent Communication, Mental and Behavioral Health, Behavior Management, Positive Behavior Support, Working With Children, Pediatrics, Mental Health Diseases and Disorders, Treatment Planning, Child Development, Disabilities

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.4K reviews

      Beginner · Course · 1 - 4 Weeks

    • J

      JetBrains

      Kotlin for Java Developers

      Skills you'll gain: Kotlin, Object Oriented Programming (OOP), Java, Java Programming, Android Development, IntelliJ IDEA, Interoperability, Unit Testing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.1K reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Pennsylvania

      Computational Thinking for Problem Solving

      Skills you'll gain: Computational Thinking, Algorithms, Pseudocode, Python Programming, Data Structures, Computer Hardware, Computer Programming, Analysis, Debugging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.4K reviews

      Beginner · Course · 1 - 4 Weeks

    • M

      MathWorks

      MathWorks Computer Vision Engineer

      Skills you'll gain: Computer Vision, Image Analysis, Anomaly Detection, Deep Learning, Applied Machine Learning, Artificial Neural Networks, Matlab, Application Deployment, PyTorch (Machine Learning Library), Machine Learning, Motion Graphics, Data Visualization, Automation, Data Mapping, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Spatial Data Analysis, Predictive Modeling, Visualization (Computer Graphics), Data Synthesis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      299 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • J

      Johns Hopkins University

      Advanced Methods in Machine Learning Applications

      Skills you'll gain: Unsupervised Learning, Applied Machine Learning, Dimensionality Reduction, Reinforcement Learning, Regression Analysis, Machine Learning, Data Mining, Machine Learning Algorithms, Statistical Machine Learning, Advanced Analytics, Predictive Modeling, Random Forest Algorithm, Decision Tree Learning, Supervised Learning

      Intermediate · Course · 1 - 3 Months

    • U

      University of Colorado Boulder

      Spacecraft Dynamics and Control

      Skills you'll gain: Control Systems, Vibrations, Mechanics, Torque (Physics), Linear Algebra, Numerical Analysis, Engineering Calculations, Simulations, Engineering Analysis, Physics, Mathematical Modeling, Visualization (Computer Graphics), Differential Equations, Simulation and Simulation Software, Applied Mathematics, Verification And Validation, Engineering, Advanced Mathematics, Estimation, Matlab

      4.8
      Rating, 4.8 out of 5 stars
      ·
      427 reviews

      Advanced · Specialization · 3 - 6 Months

    • P

      Peking University

      Chinese for HSK 1

      Skills you'll gain: Language Learning, Language Competency, Oral Expression, Literacy, Vocabulary, Grammar, Oral Comprehension

      4.9
      Rating, 4.9 out of 5 stars
      ·
      2.5K reviews

      Beginner · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      Introduction to Generative AI for Software Development

      Skills you'll gain: Prompt Engineering, Large Language Modeling, ChatGPT, Generative AI, Code Review, Software Development, Program Development, Software Development Methodologies, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML)

      4.7
      Rating, 4.7 out of 5 stars
      ·
      437 reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      IBM

      IBM AI Enterprise Workflow

      Skills you'll gain: Feature Engineering, Data Visualization, Data Ethics, Exploratory Data Analysis, Unsupervised Learning, Data Presentation, Tensorflow, Application Deployment, Dimensionality Reduction, MLOps (Machine Learning Operations), Apache Spark, Statistical Hypothesis Testing, Supervised Learning, Data Pipelines, Design Thinking, Dashboard, Unit Testing, Artificial Neural Networks, Data Science, Artificial Intelligence

      4.3
      Rating, 4.3 out of 5 stars
      ·
      319 reviews

      Advanced · Specialization · 3 - 6 Months

    • U

      University of Pennsylvania

      Introduction to Python Programming

      Skills you'll gain: Data Structures, Programming Principles, Python Programming, Computer Programming, Computational Thinking, Scripting, Software Development Tools, Integrated Development Environments, Data Import/Export, Jupyter, File Management

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.2K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free
      T

      The University of Hong Kong

      Implant Dentistry

      Skills you'll gain: Dental Procedures, Dentistry, Treatment Planning, Surgical Suturing, Oral and Dental Care, Patient Evaluation, Dental Care, Patient Treatment, Surgery, Oral Health, Medical Equipment and Technology, Biology, Health Technology, Radiography, Emerging Technologies, Risk Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.6K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free
      Free
      D

      Deep Teaching Solutions

      تعّلم كيف تتعلم: أدوات ذهنية قوية لمساعدتك على إتقان موضوعات صعبة

      Skills you'll gain:

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2.2K reviews

      Mixed · Course · 1 - 4 Weeks

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

    • ADHD: Everyday Strategies for Elementary Students: University at Buffalo
    • Kotlin for Java Developers: JetBrains
    • Computational Thinking for Problem Solving: University of Pennsylvania
    • MathWorks Computer Vision Engineer: MathWorks
    • Advanced Methods in Machine Learning Applications: Johns Hopkins University
    • Spacecraft Dynamics and Control: University of Colorado Boulder
    • Chinese for HSK 1: Peking University
    • Introduction to Generative AI for Software Development: DeepLearning.AI
    • IBM AI Enterprise Workflow: IBM
    • Introduction to Python Programming: University of Pennsylvania

    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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