BA4845 MACHINE LEARNING FOR FINANCE
| Course Code: |
3124845 |
| METU Credit (Theoretical-Laboratory hours/week): |
3(3-0) |
| ECTS Credit: |
6.0 |
| Department: |
Business Administration |
| Language of Instruction: |
English |
| Level of Study: |
Undergraduate |
| Course Coordinator: |
|
| Offered Semester: |
Fall and Spring Semesters. |
| Prerequisite: |
Set 1: 3122802
Set 2: 3122803
Set 3: 3125802
Set 4: 3160381
Set 5: 3110311
Set 6: 3110312
Set 7: 9700521 |
| One of the sets above should be completed before taking
BA4845 MACHINE LEARNING FOR FINANCE . |
Course Content
This course begins with the fundamentals of Python programming. providing students with the skills needed for data analysis. visualization. and manipulation using essential libraries such as Pandas. NumPy. and Matplotlib. It is designed as a comprehensive introduction to the application of machine learning in finance for students with no prior programming or data science experience. Students will then progress to core machine learning concepts. including regression. classification. and model validation. all taught within a financial context. The second half of the course focuses on the unique challenges and advanced techniques specific to financial data. such as market prediction. risk assessment. and sentiment analysis. The course culminates in a final project where students will build and evaluate a complete financial machine learning model. moving from raw data to actionable insights.
