The course is designed to expose students to the theory and applications of game theory, queuing models, inventory and network optimisation.
- Lecturer: Prof Sunday A. Reju
NUST eLearning
Search results: 1331
- Lecturer: Aili Ashipala
Category: S2_2025_FEBE_MME
- Lecturer: Toini Angula
Category: Architecture and the Built Environment
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- Lecturer: Dr Madelein Stoffberg
- Lecturer: Maria Indongo
- Lecturer: Selma Gwangapi Naanda
This course aims to provide students with knowledge and skills to assess the different spatial planning systems and methods currently applied in Namibia on local and regional level. Students will be able to identify both strengths and shortcomings of the present spatial planning practice under consideration of the existing legal and socio-economic framework.
- Lecturer: Dr Laudika Kandjinga
- Lecturer: Jan Swartz
- Lecturer: Dr Maliata Wanga
Category: Agricultural Sciences & Agribusiness
- Lecturer: Prof Teresia Kaulihowa
Category: Accounting Economics & Finance
This course aims at equipping students with an advanced understanding of urban ecology and the ability to successfully integrate this into urban and architectural projects ensuring a balanced and sustainable interaction between human land use and natural ecosystems.
- Lecturer: Dr Madelein Stoffberg
This is an advanced course in Property valuation. It involves application of valuation principles, appropriate techniques and method to carry out valuation of specialized properties. Topics include Agricultural Valuations, Valuation of Plant and machinery, valuation for compulsory purchase/expropriation, valuation for rating and business valuation techniques.
- Lecturer: Sam Mwando
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- Lecturer: Conrad Stoffberg
Category: Architecture and the Built Environment
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- Lecturer: Esther Calunga
Category: Architecture and the Built Environment
- Lecturer: Conrad Stoffberg
Category: Architecture and the Built Environment
The aim of this course is to introduce students to various historical periods and styles of architecture through exemplary buildings and landscapes with special focus on context; critical thinking and analysis; stimulating students’ interest in architecture and the possibilities of design.
Additionally, the course encourages the perception of architecture and design as a response to the social, natural and built environment context, while allowing students to make informed and contextually sensitive design decisions.here...
- Lecturer: Sophia Van Greunen
Category: Architecture and the Built Environment
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
Category: S1_2025_FCI
- Lecturer: Henrietha Beukes
- Lecturer: Dr Kristofina Junias
- Lecturer: Linda Kambonde
- Lecturer: Julius Kuhatumwa