Data Analysis with Machine Learning
Course Code
FI3271
Number of Credits
3
Semester
Course Type
Study Material
| Study Material | Depth |
|---|---|
| Computational thinking and algorithm design | Express |
| Learning machine concepts: supervised learning and unsupervised learning | Expert |
| Probability distribution | Expert |
| Linear models for regression and classification | Expert |
| Sampling method | Expert |
| Artificial neural networks | Expert |
| Gaussian regression for atomic force field training | Express |
| Genetic algorithms and evolution | Express |
| Bayesian Optimization | Express |
Graduate Learning Outcomes (GLO) carried by the course
| CPMK Code | Course Learning Outcomes Elements (CLO) |
|---|---|
| CPMK 1 | Able to explain the basic concepts of computational thinking |
| CPMK 2 | Designing algorithms for solving physical system problems and processing data |
| CPMK 3 | Implementing machine learning methods for analyzing physical problem data |
| CPMK 4 | Able to report the results of scientific work in oral and written form |
| CPMK 5 | Able to work effectively, both individually and in groups |
Learning Method
- Lectures, group discussions
Learning Modality
- Synchronous offline, asynchronous mixed/online
Assessment Methods
- Midterm Exam, Final Exam, Assignments, and Quizzes