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Guided Tour of Machine Learning in Finance

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Course Features

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Duration

24 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Teaching Type

Self Paced

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Video Content

24 hours

Course Description

This course is an introduction to Machine Learning, with a special focus on Finance applications. The capstone project employs supervised machine learning methods for predicting bank closings. You can take this course separately or it will give you a preview of the topics in the next modules in the specialization Machine Learning & Reinforcement Learning In Finance.

A guided tour of Machine Learning in Finance will give you an understanding of Machine Learning and its purpose.

Course Overview

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Virtual Labs

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International Faculty

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Case Based Learning

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Post Course Interactions

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Case Studies,Hands-On Training,Instructor-Moderated Discussions

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Case Studies, Captstone Projects

Skills You Will Gain

What You Will Learn

Gradient Descent Optimization

Logistic Regression for Modeling Bank Failures

Machine Learning as a Foundation of Artificial Intelligence

Overfitting and Model Capacity

Regression and Equity Analysis

Target Students

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

Experience with Python (including numpy, pandas, and IPython/Jupyter notebooks), linear algebra, basic probability theory and basic calculus is necessary to complete assignments in this course

Practitioners working at financial institutions such as banks, asset management firms or hedge funds Individuals interested in applications of ML for personal day trading

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