
Course Schedule
FTA 4005 01 — Intro to Financial Data Analyt
CRN 51356
3.0 credit hours
This course provides the foundation for financial data analytics used in business and FinTech applications. The objective of this course is for students to gain experience in analyzing financial data using modern machine learning techniques, statistical methods, and prediction models. Students will develop computational skills to perform data analysis using a modern statistical programming environment, and apply these skills to address a range of problems encountered by business firms, including those in the FinTech industry. The topics discussed include an introduction to R language, visualization of financial data, cluster analysis, simple and multiple linear regression, classification models, high dimension data analysis using Lasso, and model assessment and selection using cross validation. Students will have hands-on experience in the development of data analytics applications to analyze real world financial problems.
Course Details
College | Business | Instructor | Staff, Unknown |
---|---|---|---|
Location | Online Course | Seats Available |
2 open
|
Instructional Method | Entirely at a distance This course is delivered 100% through distance education technology. No visits to campus/designated instructional site are required. | Waitlist Available | No Waitlist Available |
Schedule Type | Asynchronous Instruction Asynchronous Course: Instruction delivered online without specified meeting days, times, or location. | Material Cost | $0 |
Semester | Summer 2025 | University Store | Online |
Term | eCore/GOML Short Session 1 | Course Fees | N/A |
Additional Information
This 8-week course is taught completely online through eMajor and moves at an accelerated pace. This course utilizes free digital resources in lieu of a textbook. This is an 8 week course and requires an introductory quiz.
Prior Approval Required: Department Approval
Meeting Times
Dates | Days | Time | Building | Room |
---|---|---|---|---|
May 19 - July 17, 2025 | - | - | - | - |