Artificial Intelligence
Course Code
IF3170
Number of Credits
4
Semester
Course Type
Related Courses
| No | Code | Course | Relation |
|---|---|---|---|
| 1 | IF3170 | Artificial Intelligence | Equivalent |
Study Material
| Study Material | Depth |
|---|---|
| DS-DG-7. Data cleaning | Explore |
| DS-DG-3. Working with various types of data | Express |
| DS-DG-2. Information extraction | Express |
| DS-DG-1. Data acquisition | Express |
| CS-IS-2. Basic Search Strategies | Expert |
| CS-IS-3. Basic Knowledge Representation and Reasoning | Expert |
| CS-IS-4. Basic Machine Learning | Expert |
| CS-IS-5. Advanced Search | Express |
| CS-IS-6. Advanced Representation and Reasoning | Expert |
| CS-IS-7. Reasoning Under Uncertainty | Express |
| CS-IS-10. Advanced Machine Learning | Express |
| DS-DM-1. Proximity measurement | Express |
| DS-DM-5. Classification and regression | Expert |
| DS-ML-1. General | Expert |
| DS-ML-2. Supervised learning | Explore |
| DS-ML-3. Unsupervised learning | Explore |
| DS-DG-4. Data integration | Expert |
| DS-DG-5. Data reduction and compression | Expert |
| DS-DG-6. Data transformation | Express |
| CS-IS-1. Fundamental Issues | Expert |
Graduate Learning Outcomes (GLO) carried by the course
| CPMK Code | Course Learning Outcomes Elements (CLO) |
|---|---|
| CPMK 1 | Explain categories of applications based on intelligent systems and those that are not. |
| CPMK 2 | Explain appropriate techniques to solve problems with specific characteristics |
| CPMK 3 | Explain the analysis results of techniques in intelligent systems and implement the selected technique on a problem |
Learning Method
- Lectures, Presentations, Project-based study, Group work, Tutorials
Learning Modality
- Online/Offline Synchronous/Asynchronous Independent/Group
Assessment Methods
- Mid-term exams, final exams, quizzes, assignments