Fundamental of Intelligent Control System
Course Code
EL4032
Number of Credits
3
Semester
Course Type
Study Material
| Study Material | Depth |
|---|---|
| Introduction | Explore |
| Machine Learning : Supervised vs Unsupervised | Explore |
| Regression | Expert |
| Classification | Expert |
| Overfitting Phenomenon and Regularization | Expert |
| Artificial Neural Network | Expert |
| Multilayer Perceptron | Express |
| Deep Neural Networks (Convolutional Neural Networks) | Expert |
| Performance evaluation | Expert |
| Artificial Neural Networks for Identification System and Control | Explore |
Graduate Learning Outcomes (GLO) carried by the course
| CPMK Code | Course Learning Outcomes Elements (CLO) |
|---|---|
| CPMK 1 | Able to understand and apply machine learning algorithms for regression and classification |
| CPMK 2 | Able to evaluate machine learning performance |
| CPMK 3 | Able to build non-parametric model of simple systems based on artificial neural networks and its utilization in control systems |
Learning Method
- Lectures, Discussions, Case Studies, Independent Study
Learning Modality
- Offline, Online, Hybrid
Assessment Methods
- Assignment, Exam, Presentation