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 modules can also be taken individually to improve relevant skills in a particular area of applications of ML to finance.

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.

Individuals interested in applications of ML for personal day trading.

Practitioners working at financial institutions such as banks, asset management firms or hedge funds.

The specialization is designed for three categories of students (3) successfully implementing a solution, and assessing its performance. (2) choosing particular ML approach(es) that would be most appropriate for resolving the problem, and (1) mapping the problem on a general landscape of available ML methods, The specialization aims at helping students to be able to solve practical ML-amenable problems that they may encounter in real life that include: 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. Extend your expertise of algorithms and tools needed to predict financial markets.Ĭompare ML for Finance with ML in Technology (image and speech recognition, robotics, etc.)ĭescribe linear regression and classification models and methods of their evaluationĮxplain how Reinforcement Learning is used for stock tradingīecome familiar with popular approaches to modeling market frictions and feedback effects for option trading. Reinforce Your Career: Machine Learning in Finance. Genre: eLearning | Language: English + srt | Duration: 143 Lessons ( 19h 32m ) | Size: 3.2 GB

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