Computational Science Methods
Course Code
SK5001
Number of Credits
2
Semester
Course Type
Related Courses
| No | Code | Course | Relation |
|---|---|---|---|
| 1 | SK5002 | Algorithm and Software Design | Equivalent |
Study Material
| Study Material | Depth |
|---|---|
| Introduction to Computational Science and Modeling | Explore |
| Dynamic system modeling | Expert |
| Force and motion modeling | Expert |
| Modeling dynamic systems with interactions | Expert |
| Errors and Simulation techniques | Expert |
| Data-driven models | Expert |
| Monte Carlo and Random walk simulations | Expert |
| Cellular Automata Model (diffusion, flame spread, and ant movement) | Expert |
| Advanced topics | Express |
Graduate Learning Outcomes (GLO) carried by the course
| CPMK Code | Course Learning Outcomes Elements (CLO) |
|---|---|
| CPMK 1 | Students have basic computational science skills |
| CPMK 2 | Students have the ability to solve problems in computational science |
| CPMK 3 | Students are able to produce computational solutions to problems that arise in science |
Learning Method
- Lectures, discussions, research/problem/case study based learning, literature studies, group/independent work, presentations, practice
Learning Modality
- Offline/online/hybrid, synchronous and asynchronous
Assessment Methods
- Assessment is given through Homework / Assignments / Quizzes / Practicum / RBL / Reports / Presentations / UTS / UAS