Guided Tour of Machine Learning in Finance
Course Features
Duration
24 hours
Delivery Method
Online
Available on
Limited Access
Accessibility
Desktop, Laptop
Language
English
Subtitles
English
Level
Intermediate
Teaching Type
Self Paced
Video Content
24 hours
Course Description
Course Overview
Virtual Labs
International Faculty
Case Based Learning
Post Course Interactions
Case Studies,Hands-On Training,Instructor-Moderated Discussions
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