Artificial Intelligence for Finance
CSE-41349
The course aims at helping students to understand Fintech and solve practical AI problems they may encounter in field of finance. The course is designed for practitioners working at financial institutions such as banks, asset management firms or hedge funds, individuals interested in applications of AI for personal trading/portfolio management and current students pursuing a degree in Finance, Statistics, Computer Science, Mathematics or other related disciplines who want to learn practical applications of AI in Finance.
A learner with some or no previous knowledge of AI/Machine Learning (ML) will get to know main algorithms of Supervised and Unsupervised Learning and including different sources of data. We will use AI open source Python/TensorFlow packages to design, test, and implement different AI algorithms in Finance. The theory, concepts, and codebase covered in this course will be extremely useful at every step of the model development life cycle, from idea generation to model implementation.
Course Highlights:
- Understand different financial data sources
- Learn how to map the practical problem to available AI methods
- Understand which particular AI model would be most appropriate for resolving the problem
- Acquire ability to successfully implement a solution, and assess its performance
Course Learning Outcomes:
- Understanding different financial data sources
- Learn to map the practical problem to available AI methods
- Determine which particular AI model would be most appropriate for resolving the problem, and
- Gain knowledge to be able to successfully implement a solution, and assess its performance
Course Typically Offered: Online in Summer quarters
Next Step: After completing this course, consider taking additional coursework in the Machine Learning Methods and Technical Aspects of Artificial Intelligence certificate program
Contact: For more information about this course, please email unex-techdata@ucsd.edu
Course Information
Course sessions
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This course is entirely web-based and to be completed asynchronously between the published course start and end dates. Synchronous attendance is NOT required.
You will have access to your online course on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.
Textbooks:
All course materials are included unless otherwise stated.
Policies:
- No refunds after: 6/30/2025
