Machine Learning for Telecommunications
Course Code
ET2204
Number of Credits
3
Semester
4
Course Type
C
Related Courses
| No | Code | Course | Relation |
|---|---|---|---|
| 1 | ET3107 | Advanced Programming | Equivalent |
| 2 | ET1203 | Programming | Prerequisite |
Study Material
| Study Material | Depth |
|---|---|
| Verbal communication | |
| Engineering Design | Express |
| Simulation and modeling | Expert |
| Classification, regression, dimensionality reduction & clustering | Expert |
Graduate Learning Outcomes (GLO) carried by the course
| CPMK Code | Course Learning Outcomes Elements (CLO) |
|---|---|
| CPMK 1 | Ability to apply scientific and mathematical relationships (principles or laws) and inputs required for Simulation and Modeling, Classification, Regression, and Dimension Reduction |
| CPMK 2 | Ability to analyze problems / identify opportunities to produce simulation and modeling design problem statements for Simulation and Modeling, Classification, Regression, and Dimension Reduction |
| CPMK 3 | Ability to identify constraints to produce design requirements in Simulation and Modeling, Classification, Regression, and Dimension Reduction |
| CPMK 4 | Ability to identify and formulate technical problems in Simulation and Modeling, Classification, Regression and Dimension Reduction |
| CPMK 5 | Ability to analyze and solve technical problems dealing with Simulation and Modeling, Classification, Regression and Dimension Reduction |
Learning Method
- Lecture Group discussion Problem/Case Study based learning
Learning Modality
- Luring Sinkron Daring Asinkron Hybrid
Assessment Methods
- Quizzes, Mid-Semester Exams, Final Exam