- Lecturer: Dr Gereon Koch Kapuire
- Lecturer: Rosetha Kays
- Lecturer: Dr Gabriel Nhinda
- Lecturer: Prof Heike Winschiers-Theophilus
- Lecturer: Naftali Indongo
- Lecturer: Prof Heike Winschiers-Theophilus
- Lecturer: Shilumbe Chivuno-Kuria
- Lecturer: KEITH KASIKA
- Lecturer: TJIHIMISE KAUNATJIKE
- Lecturer: NYASHA MUSIYARIRA
- Lecturer: LAURINDA NDJAO
- Lecturer: Andrew Tjirare

Learning Outcomes
Upon successful completion of the course, the student should be able to:
- Use Artificial Intelligence (AI) techniques to map problem domains into suitable models for effective and efficient processing;
- Evaluate the efficiency and applicability of different AI concepts, models, and algorithms in a specific problem domain;
- Implement AI algorithms.
Course Content
Search Algorithms
- Search, Beyond classical search and Adversarial search
- Constraint Satisfaction and Optimisation
Knowledge, Reasoning and Planning
- Knowledge Representation and Inference
- Classical Planning
- Markov Decision Processes
Machine Learning
- Reinforcement Learning
- Deep Learning
- Lecturer: Naftali Indongo