BIN517 STATISTICAL LEARNING FOR BIOINFORMATICS
| Course Code: |
9080517 |
| METU Credit (Theoretical-Laboratory hours/week): |
3(3-0) |
| ECTS Credit: |
8.0 |
| Department: |
Bioinformatics |
| Language of Instruction: |
English |
| Level of Study: |
Graduate |
| Course Coordinator: |
|
| Offered Semester: |
Fall and Spring Semesters. |
| Prerequisite: |
Set 1: 5710230
, 5710240 , 9080500 |
| The course set above should be completed before taking
BIN517 STATISTICAL LEARNING FOR BIOINFORMATICS. |
Course Content
This course covers key concepts in statistical learning, specifically regression, classification, resampling methods, linear model selection, regularization; moves beyond linearity; explores tree-based methods, support vector machines, deep learning, survival analysis, unsupervised learning, and multiple testing. Course provides all these concepts and showcase them through Jupyter notebooks, which allow to run Python code. This course is comprehensive in terms of statistical learning methods it covers and focused on the applications of these methods in Python.
