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.
от партнера
Чему вы научитесь
Compare ML for Finance with ML in Technology (image and speech recognition, robotics, etc.)
Describe linear regression and classification models and methods of their evaluation
Explain how Reinforcement Learning is used for stock trading
Become familiar with popular approaches to modeling market frictions and feedback effects for option trading.
Приобретаемые навыки
Специализация: общие сведения
Проект прикладного обучения
The specialization is essentially in ML where all examples, home assignments and course projects deal with various problems in Finance (such as stock trading, asset management, and banking applications), and the choice of topics is respectively driven by a focus on ML methods that are used by practitioners in Finance. The specialization is meant to prepare the students to work on complex machine learning projects in finance that often require both a broad understanding of the whole field of ML, and understanding of appropriateness of different methods available in a particular sub-field of ML (for example, Unsupervised Learning) for addressing practical problems they might encounter in their work.
Basic math including calculus and linear algebra, basic probability theory and statistics, and programming skills in Python.
Basic math including calculus and linear algebra, basic probability theory and statistics, and programming skills in Python.
Специализация включает несколько курсов: 4
Guided Tour of Machine Learning in Finance
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 can be taken as a separate course, it serves as a preview of topics that are covered in more details in subsequent modules of the specialization Machine Learning and Reinforcement Learning in Finance.
Fundamentals of Machine Learning in Finance
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 which particular ML approach(es) would be most appropriate for resolving the problem, and (3) ability to successfully implement a solution, and assess its performance.
Reinforcement Learning in Finance
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.
Overview of Advanced Methods of Reinforcement Learning in Finance
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.
от партнера

New York University
New York University is a leading global institution for scholarship, teaching, and research. Based in New York City with campuses and sites in 14 additional major cities across the world, NYU embraces diversity among faculty, staff and students to ensure the highest caliber, most inclusive educational experience.
Часто задаваемые вопросы
Какие правила возврата средств?
Можно ли зарегистрироваться только на один курс?
Можно ли получить финансовую помощь?
Могу ли я пройти курс бесплатно?
Действительно ли это полностью дистанционный курс? Нужно ли мне посещать какие-либо занятия лично?
Получу ли я зачеты в университете за прохождение специализации?
Получу ли я зачеты в университете за прохождение специализации?
Остались вопросы? Посетите Центр поддержки учащихся.