General Information
Instructor(s)
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- Finance (s)
- Funds Management (r)
- Management Analytics (c)
- Risk Management and Financial Engineering (c)
Target Audience
Machine learning is an important branch of artificial intelligence where a computer learns from large volumes of data. Many activities within financial services (as well as other industries) are being impacted by machine learning. For example, lending decisions, investment strategies, fraud detection, the marketing of financial products, and even hiring decisions now involve machine lending. If you are hoping to get a job in finance, you should seriously consider taking this course. Machine learning and artificial intelligence are likely to have a big impact on your career.
Format
12 regular sessions
Course Mission
Students will understand enough about machine learning to be able to work with data science specialists. This is likely to be an essential skill for finance professionals in the future. The course will cover the main techniques used by data scientists to handle large data sets for prediction, clustering, and interacting with a changing environment.
Python is currently the language of choice for machine learning and is now widely used in business. There will be a Python module offered by FinHub. Unless they are already Python users, students who register for this course should plan to complete this module before the course starts. As many people have pointed out, “Python is the new Excel”. It is becoming impossible to get many jobs without having Python on your resume.
Course Scope
The course will introduce students to the tools of machine learning and allow them to become comfortable with the way Python is used for machine learning projects. They will undertake some assignments on their own and larger projects in groups. There will be group presentations involving a variety of innovations that are changing the financial sector.
Evaluation and Grade Breakdown
| Component | Weight |
|---|---|
| Class Participation | 10% |
| Individual Assignments | 20% |
| Group Projects | 20% |
| Class Presentations | 10% |
| Final Exam (during final exam period) | 40% |
Required Resources
“Machine learning in Business: An Introduction to the World of Data Science” 3rd edition, 2021, John Hull.
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