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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

      Accelerate Terraform Development with GitHub Copilot and AI

      Skills you'll gain: Infrastructure as Code (IaC), Terraform, Development Environment, DevOps, Integrated Development Environments, Software Development Tools, GitHub, Generative AI, Git (Version Control System), Artificial Intelligence

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      P

      Packt

      Scene Detailing, Prop Creation, and Rendering

      Skills you'll gain: 3D Modeling, Computer Graphics, Virtual Environment, Visualization (Computer Graphics), Technical Design, Performance Tuning, Design, Aesthetics

      Intermediate · Course · 3 - 6 Months

    • Status: New
      New
      G

      Google Cloud

      Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation - 繁體中文

      Skills you'll gain: Generative AI, Continuous Monitoring, MLOps (Machine Learning Operations), Predictive Modeling, Google Cloud Platform, System Monitoring, Machine Learning, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Data Ethics, Data Quality, Automation

      Intermediate · Course · 1 - 4 Weeks

    • U

      Universidad de los Andes

      Maestría en Inteligencia Artificial

      Skills you'll gain: Supervised Learning, Unsupervised Learning, Anomaly Detection, Computer Vision, Reinforcement Learning, Cloud-Native Computing, Natural Language Processing, Containerization, Deep Learning, Dimensionality Reduction, Artificial Intelligence, Machine Learning, CI/CD, Probability & Statistics, Data Ethics, Embedded Systems, Application Deployment, Game Theory, Epidemiology, Automation

      Earn a degree

      Degree · 1 - 4 Years

    • G

      Google Cloud

      Responsible AI for Developers: Fairness & Bias - Українська

      Skills you'll gain: Data Ethics, Artificial Intelligence, Google Cloud Platform, Machine Learning, MLOps (Machine Learning Operations), Data Validation

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      G

      Google Cloud

      Menggunakan BigQuery Machine Learning untuk Inferensi

      Skills you'll gain:

      Beginner · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Responsible AI for Developers: Fairness & Bias - Polski

      Skills you'll gain: Data Ethics, Artificial Intelligence, Artificial Intelligence and Machine Learning (AI/ML), Open Source Technology, Google Cloud Platform, Machine Learning, Data Cleansing, Machine Learning Methods

      Intermediate · Course · 1 - 3 Months

    • P

      Pontificia Universidad Católica de Chile

      Certificado en Introducción a la Ciencia de Datos

      Skills you'll gain: Predictive Analytics, Unsupervised Learning, Data Cleansing, Exploratory Data Analysis, Dimensionality Reduction, Data Science, Descriptive Analytics, Supervised Learning, Regression Analysis, Visualization (Computer Graphics), Data Visualization, Machine Learning Algorithms, Data-Driven Decision-Making, Data Processing, Time Series Analysis and Forecasting, Data Visualization Software, Statistical Machine Learning, Statistical Visualization, Machine Learning, Matplotlib

      Credit offered

      Mastertrack · 6 - 12 Months

    • P

      Pontificia Universidad Católica de Chile

      Magíster en Business Analytics

      Skills you'll gain: Revenue Management, Customer Analysis, Descriptive Analytics, FinTech, Database Design, People Analytics, Time Series Analysis and Forecasting, Biostatistics, Predictive Analytics, Statistical Reporting, Digital Transformation, Deep Learning, Risk Analysis, Bayesian Statistics, Cloud Security, Network Model, Assertiveness, Web Scraping, Governance, Business Process Modeling

      Earn a degree

      Degree · 1 - 4 Years

    • U

      University of Colorado Boulder

      Master of Science in Data Science

      Skills you'll gain: Object Oriented Design, User Story, SQL, Systems Engineering, New Product Development, Field-Programmable Gate Array (FPGA), Strategic Decision-Making, Delegation Skills, Sampling (Statistics), Failure Analysis, Diversity Equity and Inclusion Initiatives, Supplier Management, Sustainability Reporting, Data Ethics, Data Mining, Statistical Modeling, Unsupervised Learning, Goal Setting, Proposal Writing, Generative AI

      Earn a degree

      Degree · 1 - 4 Years

    • U

      University of Colorado Boulder

      Power Electronics Graduate Certificate

      Skills you'll gain: Power Electronics, Debugging, Tensorflow, Computer Vision, Display Devices, Computer Displays, Image Analysis, Semiconductors, Electrical Engineering, Engineering Documentation, Electronic Systems, Systems Design, Artificial Neural Networks, Applied Machine Learning, USB, Software Design Documents, Computer Programming Tools, Technical Design, Test Engineering, Deep Learning

      Credit offered

      Graduate Certificate · 6 - 12 Months

    • U

      University of Leeds

      Master of Science in Data Science (Statistics)

      Skills you'll gain: Data Ethics, Regression Analysis, Unsupervised Learning, Statistical Hypothesis Testing, Correlation Analysis, Statistical Machine Learning, Data Visualization, Statistical Methods, Classification And Regression Tree (CART), Exploratory Data Analysis, Planning, Applied Machine Learning, Machine Learning Methods, Data Visualization Software, Bayesian Statistics, Dimensionality Reduction, Supervised Learning, Box Plots, Statistical Modeling, Data Analysis

      Earn a degree

      Degree · 1 - 4 Years

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

    • Accelerate Terraform Development with GitHub Copilot and AI: Packt
    • Scene Detailing, Prop Creation, and Rendering: Packt
    • Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation - 繁體中文: Google Cloud
    • Maestría en Inteligencia Artificial: Universidad de los Andes
    • Responsible AI for Developers: Fairness & Bias - Українська: Google Cloud
    • Menggunakan BigQuery Machine Learning untuk Inferensi: Google Cloud
    • Responsible AI for Developers: Fairness & Bias - Polski: Google Cloud
    • Certificado en Introducción a la Ciencia de Datos: Pontificia Universidad Católica de Chile
    • Magíster en Business Analytics: Pontificia Universidad Católica de Chile
    • Master of Science in Data Science: University of Colorado Boulder

    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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