Foundations of Artificial Intelligence
Course Code
IF3070
Number of Credits
3
Semester
5
Course Type
C
Study Material
| Study Material | Depth |
|---|---|
| CS-IS-1. Fundamental Issues | Expert |
| DS-DM-5. Classification and regression | Expert |
| DS-DM-1. Proximity measurement | Express |
| CS-IS-7. Reasoning Under Uncertainty | Express |
| CS-IS-5. Advanced Search | Express |
| CS-IS-6. Advanced Representation and Reasoning | Expert |
| CS-IS-4. Basic Machine Learning | Expert |
| CS-IS-3. Basic Knowledge Representation and Reasoning | Expert |
| DS-ML-1. General | Expert |
| DS-ML-3. Unsupervised learning | Expert |
| DS-ML-2. Supervised learning | Expert |
| CS-IS-2. Basic Search Strategies | Expert |
Graduate Learning Outcomes (GLO) carried by the course
| CPMK Code | Course Learning Outcomes Elements (CLO) |
|---|---|
| CPMK 1 | Explains the categories of applications that are based on intelligent systems and those that are not. |
| CPMK 2 | Explain the appropriate techniques for solving problems with certain characteristics. |
| CPMK 3 | Explain the results of the analysis of techniques in intelligent systems and implement the selected technique to 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