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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: New
      New
      P

      Packt

      Network Fundamentals & Cisco Platform Development

      Skills you'll gain: Network Troubleshooting, Computing Platforms, Network Administration, General Networking, Software-Defined Networking, OSI Models, TCP/IP, Networking Hardware, Network Infrastructure, Network Model, Restful API, Network Protocols, Network Switches, Scripting, Application Programming Interface (API)

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      Status: Free
      Free
      C

      Coursera Instructor Network

      GenAI for Employee Engagement: Driving Real-Time Insights

      Skills you'll gain: Employee Engagement, Drive Engagement, HR Tech, People Analytics, AI Personalization, Generative AI, Employee Surveys, Human Resource Strategy, Employee Retention, Data Ethics, Real Time Data, Human Resources, User Feedback, Continuous Improvement Process

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Responsible AI for Developers: Interpretability & Transparency - Italiano

      Skills you'll gain: Data Ethics, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), MLOps (Machine Learning Operations), Machine Learning, Data Integrity, Artificial Intelligence, Technical Documentation, Data Governance

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Responsible AI: Interpretability & Transparency - Deutsch

      Skills you'll gain: Data Ethics, Data Analysis, Data Science, Analysis, Applied Machine Learning, Data Visualization Software, Artificial Intelligence, Machine Learning, Technical Communication

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Responsible AI for Developers: Fairness & Bias - 繁體中文

      Skills you'll gain: Data Ethics, Artificial Intelligence, Google Cloud Platform, Open Source Technology, Data Quality, Data Validation, Machine Learning

      Intermediate · Course · 1 - 3 Months

    • G

      Google Cloud

      Responsible AI for Developers: Privacy & Safety - Français

      Skills you'll gain: Information Privacy, Cloud Security, Generative AI, Personally Identifiable Information, Google Cloud Platform, Data Security, Artificial Intelligence, Safety and Security, Encryption, Machine Learning

      Intermediate · Course · 1 - 3 Months

    • G

      Google Cloud

      Encoder-Decoder Architecture - Deutsch

      Skills you'll gain: Keras (Neural Network Library), Tensorflow, Applied Machine Learning, Deep Learning, Natural Language Processing, Artificial Neural Networks, Machine Learning Methods

      Advanced · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Work with Gemini Models in BigQuery - 한국어

      Skills you'll gain: Generative AI, Customer Relationship Management, Workflow Management, Google Cloud Platform, Applied Machine Learning, Big Data, Business Modeling, Artificial Intelligence and Machine Learning (AI/ML), SQL, Predictive Modeling, Python Programming

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      P

      Packt

      Microsoft Sentinel Advanced Course - Secure Azure Like a Pro

      Skills you'll gain: Infrastructure as Code (IaC), Microsoft Azure, Azure DevOps, Continuous Integration, Terraform, GitHub, Continuous Deployment, CI/CD, Debugging, Security Information and Event Management (SIEM), Windows PowerShell, Git (Version Control System), Data Management, Automation

      Advanced · Course · 1 - 4 Weeks

    • Status: New
      New
      G

      Google Cloud

      BigQuery ML を推論に使用する

      Skills you'll gain:

      Beginner · Course · 1 - 4 Weeks

    • Status: New
      New
      P

      Packt

      Docker and Kubernetes Masterclass: From Beginner to Advanced

      Skills you'll gain: Kubernetes, Docker (Software), Containerization, Cloud-Native Computing, YAML, Application Deployment, Devops Tools, Google Cloud Platform, Command-Line Interface, Development Environment, Nginx, MongoDB, Configuration Management, Software Installation, Cloud Security, Infrastructure Architecture, Microservices, Data Storage, Role-Based Access Control (RBAC), General Networking

      Intermediate · Specialization · 3 - 6 Months

    • G

      Google Cloud

      Work with Gemini Models in BigQuery - 繁體中文

      Skills you'll gain: Generative AI, Google Cloud Platform, Big Data, Customer Relationship Management, SQL, Business Modeling, Artificial Intelligence and Machine Learning (AI/ML), Data Analysis, Natural Language Processing

      Intermediate · Course · 1 - 4 Weeks

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

    • Network Fundamentals & Cisco Platform Development: Packt
    • GenAI for Employee Engagement: Driving Real-Time Insights: Coursera Instructor Network
    • Responsible AI for Developers: Interpretability & Transparency - Italiano: Google Cloud
    • Responsible AI: Interpretability & Transparency - Deutsch: Google Cloud
    • Responsible AI for Developers: Fairness & Bias - 繁體中文: Google Cloud
    • Responsible AI for Developers: Privacy & Safety - Français: Google Cloud
    • Encoder-Decoder Architecture - Deutsch: Google Cloud
    • Work with Gemini Models in BigQuery - 한국어: Google Cloud
    • Microsoft Sentinel Advanced Course - Secure Azure Like a Pro: Packt
    • BigQuery ML を推論に使用する: Google Cloud

    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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