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    • Reinforcement Learning

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    86 results for "reinforcement learning"

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      IBM Skills Network

      Machine Learning Introduction for Everyone

      Skills you'll gain: Machine Learning, Algorithms, Data Analysis, Deep Learning, Machine Learning Algorithms, Probability & Statistics, Regression, Reinforcement Learning, Theoretical Computer Science

      4.5

      (107 reviews)

      Beginner · Course · 1-4 Weeks

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      Coursera Project Network

      XG-Boost 101: Used Cars Price Prediction

      Skills you'll gain: Applied Machine Learning, Machine Learning, Machine Learning Algorithms, Probability & Statistics, Reinforcement Learning, Python Programming, Regression

      4.7

      (35 reviews)

      Intermediate · Guided Project · Less Than 2 Hours

    • Free

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      University of Washington

      Computational Neuroscience

      Skills you'll gain: Data Science, Machine Learning, Artificial Neural Networks, Python Programming, Statistical Programming, Matlab, Reinforcement Learning, Business Psychology, Communication, Computer Networking, Computer Programming, Data Analysis, Data Analysis Software, Deep Learning, Entrepreneurship, General Statistics, Linear Algebra, Machine Learning Algorithms, Mathematics, Network Model, Probability & Statistics, Probability Distribution

      4.6

      (1k reviews)

      Beginner · Course · 1-3 Months

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      New York University

      Overview of Advanced Methods of Reinforcement Learning in Finance

      Skills you'll gain: Mathematics, Applied Mathematics, Calculus, Finance, General Statistics, Investment Management, Probability & Statistics, Entrepreneurship

      3.8

      (78 reviews)

      Advanced · Course · 1-4 Weeks

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      New York University

      Reinforcement Learning in Finance

      Skills you'll gain: Advertising, Applied Machine Learning, Communication, Computer Programming, Marketing, Operations Research, Python Programming, Research and Design, Strategy and Operations, Tensorflow

      3.6

      (123 reviews)

      Advanced · Course · 1-4 Weeks

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      IBM Skills Network

      IBM Data Science

      Skills you'll gain: Python Programming, Data Science, Data Analysis, Data Structures, Statistical Programming, Machine Learning, Data Mining, Regression, Machine Learning Algorithms, Data Visualization, General Statistics, Basic Descriptive Statistics, SQL, Applied Machine Learning, Statistical Analysis, Computer Programming Tools, Data Analysis Software, Machine Learning Software, Software Visualization, Databases, Programming Principles, Exploratory Data Analysis, Computer Programming, Statistical Visualization, Algebra, Data Management, Database Theory, Data Visualization Software, R Programming, Statistical Machine Learning, Statistical Tests, Deep Learning, Probability & Statistics, Extract, Transform, Load, Plot (Graphics), Devops Tools, SPSS, Estimation, Interactive Data Visualization, Algorithms, Database Application, Geovisualization, Reinforcement Learning, Theoretical Computer Science, Big Data, Business Analysis, Computational Logic, Correlation And Dependence, Database Administration, Econometrics, Entrepreneurship, Marketing, Mathematical Theory & Analysis, Mathematics, Spreadsheet Software, Storytelling, Supply Chain Systems, Supply Chain and Logistics, Writing

      4.6

      (108.1k reviews)

      Beginner · Professional Certificate · 3-6 Months

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      DeepLearning.AI

      AI For Everyone

      Skills you'll gain: Machine Learning, Business Analysis, Applied Machine Learning, Business Transformation, Data Analysis, Data Model, Deep Learning, Exploratory Data Analysis, Forecasting, Human Computer Interaction, Natural Language Processing, People Analysis, Probability & Statistics, Reinforcement Learning, Statistical Analysis, Artificial Neural Networks, Machine Learning Algorithms

      4.8

      (37.9k reviews)

      Beginner · Course · 1-4 Weeks

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      IBM Skills Network

      IBM Machine Learning

      Skills you'll gain: Machine Learning, Probability & Statistics, General Statistics, Forecasting, Machine Learning Algorithms, Regression, Data Analysis, Deep Learning, Theoretical Computer Science, Artificial Neural Networks, Statistical Machine Learning, Algorithms, Business Analysis, Dimensionality Reduction, Exploratory Data Analysis, Feature Engineering, Computer Vision, Applied Machine Learning, Bayesian Statistics, NoSQL, Probability Distribution, Human Resources, Leadership Development, Leadership and Management, Data Management, Data Structures, Experiment, Linear Algebra, Mathematics, Computer Graphic Techniques, Computer Graphics, Computer Programming, Data Visualization, Natural Language Processing, Python Programming, Reinforcement Learning, Statistical Programming, Statistical Visualization, Algebra, Application Development, Basic Descriptive Statistics, Correlation And Dependence, Data Analysis Software, Estimation, SQL, Software Engineering, Statistical Analysis, Statistical Tests

      4.6

      (1.4k reviews)

      Intermediate · Professional Certificate · 3-6 Months

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      University of Pennsylvania

      AI For Business

      Skills you'll gain: Machine Learning, Entrepreneurship, Leadership and Management, Strategy and Operations, Machine Learning Algorithms, Finance, Data Management, Theoretical Computer Science, Business Analysis, Human Resources, Marketing, Applied Machine Learning, Data Analysis, Sales, Artificial Neural Networks, Deep Learning, Computational Thinking, Computer Programming, Accounting, Algorithms, People Management, Regulations and Compliance, Strategy, Big Data, Data Mining, Data Warehousing, Feature Engineering, Natural Language Processing, Reinforcement Learning, Audit, BlockChain, Business Transformation, Clinical Data Management, Customer Analysis, Customer Relationship Management, Customer Success, Database Administration, Databases, Decision Making, Financial Analysis, Innovation, People Analysis, Research and Design, Security Engineering, Software Security

      4.7

      (147 reviews)

      Beginner · Specialization · 3-6 Months

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      University of Pennsylvania

      AI Fundamentals for Non-Data Scientists

      Skills you'll gain: Data Management, Machine Learning, Artificial Neural Networks, Deep Learning, Machine Learning Algorithms, Applied Machine Learning, Big Data, Computational Thinking, Computer Programming, Data Analysis, Data Mining, Data Warehousing, Feature Engineering, Natural Language Processing, Reinforcement Learning, Theoretical Computer Science

      4.7

      (81 reviews)

      Mixed · Course · 1-4 Weeks

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      Google Cloud

      Customer Experiences with Contact Center AI - Dialogflow CX

      Skills you'll gain: Machine Learning, Natural Language Processing, Business Psychology, Research and Design, User Experience Design, Human Computer Interaction, Applied Machine Learning, Communication, Reinforcement Learning, Software Architecture, Software Engineering, Theoretical Computer Science, Mobile Development, Other Mobile Programming Languages, User Experience, Cloud Computing, Computer Architecture, Computer Graphics, Computer Networking, Continuous Integration, DevOps, Google Cloud Platform, Interactive Design, Network Architecture, Software As A Service, Finance, Operations Management

      4.4

      (198 reviews)

      Beginner · Specialization · 3-6 Months

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      Google Cloud

      Advanced Machine Learning on Google Cloud

      Skills you'll gain: Machine Learning, Cloud Computing, Google Cloud Platform, Cloud Platforms, Probability & Statistics, Business Psychology, General Statistics, Deep Learning, Entrepreneurship, Natural Language Processing, Statistical Programming, Apache, Cloud Applications, Data Management, Machine Learning Software, Python Programming, Reinforcement Learning, Tensorflow, Artificial Neural Networks, Computer Graphic Techniques, Computer Graphics, Computer Vision, Performance Management, Strategy and Operations, Applied Machine Learning, Cloud API, Computational Thinking, Computer Architecture, Computer Programming, Data Analysis, Data Engineering, Distributed Computing Architecture, Hardware Design, Machine Learning Algorithms, Other Cloud Platforms and Tools, Theoretical Computer Science

      4.5

      (1.4k reviews)

      Advanced · Specialization · 3-6 Months

    Searches related to reinforcement learning

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    1234…8

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

    • Machine Learning Introduction for Everyone: IBM Skills Network
    • XG-Boost 101: Used Cars Price Prediction: Coursera Project Network
    • Computational Neuroscience: University of Washington
    • Overview of Advanced Methods of Reinforcement Learning in Finance: New York University
    • Reinforcement Learning in Finance: New York University
    • IBM Data Science: IBM Skills Network
    • AI For Everyone: DeepLearning.AI
    • IBM Machine Learning: IBM Skills Network
    • AI For Business: University of Pennsylvania
    • AI Fundamentals for Non-Data Scientists: 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.‎

    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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