Специализация Machine Learning and Reinforcement Learning in Finance

Начинается Jul 02

Специализация Machine Learning and Reinforcement Learning in Finance

Reinforce Your Career: Machine Learning in Finance. Extend your expertise of algorithms and tools needed to predict financial markets.

Об этой специализации

The main goal of this specialization is to provide the knowledge and practical skills necessary to develop a strong foundation on core paradigms and algorithms of machine learning (ML), with a particular focus on applications of ML to various practical problems in Finance. The specialization aims at helping students to be able to solve practical ML-amenable problems that they may encounter in real life that include: (1) mapping the problem on a general landscape of available ML methods, (2) choosing particular ML approach(es) that would be most appropriate for resolving the problem, and (3) successfully implementing a solution, and assessing its performance. The specialization is designed for three categories of students: · Practitioners working at financial institutions such as banks, asset management firms or hedge funds · Individuals interested in applications of ML for personal day trading · Current full-time students pursuing a degree in Finance, Statistics, Computer Science, Mathematics, Physics, Engineering or other related disciplines who want to learn about practical applications of ML in Finance. The modules can also be taken individually to improve relevant skills in a particular area of applications of ML to finance.

Автор:

courses
4 courses

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Проекты

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Сертификаты

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Обзор проектов

Курсы
Intermediate Specialization.
Some related experience required.
  1. 1-Й КУРС

    Guided Tour of Machine Learning in Finance

    Upcoming session: Jul 2
    Субтитры
    English

    О курсе

    This course aims at providing an introductory and broad overview of the field of ML with the focus on applications on Finance. Supervised Machine Learning methods are used in the capstone project to predict bank closures. Simultaneously, while this course
  2. 2-Й КУРС

    Fundamentals of Machine Learning in Finance

    Upcoming session: Jul 2
    Субтитры
    English

    О курсе

    The course aims at helping students to be able to solve practical ML-amenable problems that they may encounter in real life that include: (1) understanding where the problem one faces lands on a general landscape of available ML methods, (2) understanding
  3. 3-Й КУРС

    Reinforcement Learning in Finance

    Upcoming session: Jul 2
    Субтитры
    English

    О курсе

    This course aims at introducing the fundamental concepts of Reinforcement Learning (RL), and develop use cases for applications of RL for option valuation, trading, and asset management. Prerequisites are the courses "Guided Tour of Machine Learning in Fi
  4. 4-Й КУРС

    Overview of Advanced Methods of Reinforcement Learning in Finance

    Начинается June 25th, 2018
    Субтитры
    English

    О курсе

    In the last course of our specialization, Overview of Advanced Methods of Reinforcement Learning in Finance, we will take a deeper look into topics discussed in our third course, Reinforcement Learning in Finance. In particular, we will talk about links between Reinforcement Learning, option pricing and physics, implications of Inverse Reinforcement Learning for modeling market impact and price dynamics, and perception-action cycles in Reinforcement Learning. Finally, we will overview trending and potential applications of Reinforcement Learning for high frequency trading, cryptocurrencies, peer-to-peer lending, and more.

Авторы

  • New York University Tandon School of Engineering

    New York University strives to be a quality international center of scholarship, teaching and research. As one of the nation's most respected institutions, NYU Tandon School of Engineering aligns with this mission.

    Tandon offers comprehensive courses in engineering, applied science and technology. Each course is rooted in a tradition of invention and entrepreneurship.

  • Igor Halperin

    Igor Halperin

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