- Lecturer: Charles Mbazuvara
- Lecturer: Magdaleena Nambala
- Lecturer: Cephas Pahla
- Lecturer: Dr Gloria Tshoopara
NUST eLearning
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- Lecturer: Moira Cloete
- Lecturer: Magdaleena Nambala
- Lecturer: Cephas Pahla
- Lecturer: Adri Smith
This course aims to introduce students to the fundamentals of marketing and the environments in which marketing operates and what marketing is to its relevance to the overall business process. It explains the contribution and essence of each of the four traditional and three extra elements (4+ 3 Ps) of marketing products/services and other critical concepts like segmentation and market research and intelligence in developing an effective marketing programme in response to the ever-changing customer and consumers’ demands, needs and wants in other to meet the goal of professional organisations in the areas of sports, logistics, recreation, and transport.
- Lecturer: Peter Haufiku
- Lecturer: Brenda Kahuikee
- Lecturer: Loide Moombola
- Lecturer: Selma Gwangapi Naanda
- Lecturer: John-Graftt Ndungaua
- Lecturer: Linda Kambonde
- Lecturer: Benhardt Kauteza
- Lecturer: Faith Marais
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- Lecturer: Johnson Mutirua
- Lecturer: Beatrice Mutonga
- Lecturer: Wanja Njuguna
Welcome to General Biology 1A, hoping you will have an engaging and transforming experience.
- Lecturer: Petrus Paulus
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- Lecturer: Dr Euodia Hess-Wallenstein
- Lecturer: Dr Marius Mutorwa
- Lecturer: Hamutenya Hainghumbi
- Lecturer: Rebecca Mujazu
- Lecturer: John Mukoya
- Lecturer: Frank Mulungu
- Lecturer: Jacob Orange
- Lecturer: Cephas Pahla
- Lecturer: James Van Rooi
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- Lecturer: Dr Vaino Indongo
- Lecturer: Sheelagh Ndahepele
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- Lecturer: Prof Sylvanus Onjefu
The course aims to provide students with knowledge of the types of different spatial databases. Students will also be able to design a spatial database using FOSS GIS, populate the spatial tables and perform basic spatial analysis. Other areas to be covered include ESRI geo-database types and supported elements, Working with ESRI geo-database subtypes, domains and relationship rules, ESRI geo-database Annotation: Creating, editing, and managing annotation features, ESRI geo-database Topology rules, management and editing and Utility Networks and analysis.
- Lecturer: Erich Naoseb
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- Lecturer: Ivonne Makando

Welcome to GIS 2
Get ready to explore the exciting world of geospatial data. In this course, you’ll learn how to acquire spatial data, solve real-world problems, perform basic vector analysis, and understand the importance of metadata.
This course introduces the theory and practice of basic geospatial analysis, focusing on:
- Data Acquisition – Learn how spatial data is sourced and prepared
- Spatial Problem Analysis – Use GIS to understand and solve real-world issues
- Basic Spatial Analysis (Vector) – Explore how vector data helps analyze patterns
- Metadata – Understand how data documentation supports GIS integrity
What You’ll Learn
By the end of this course, you should be able to:
- Explain spatial file formats and describe how to create/edit GIS layers
- Analyze spatial problems and evaluate GIS-based solutions
- Apply vector-based spatial analysis techniques appropriately
- Define and create metadata using standard formats and assess its quality
Recommended Reading
To support your understanding, the following textbooks are recommended:
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Principles of Geographic Information Systems, 3rd Ed. (ITC, 2004)
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Applied GIS and Spatial Analysis, by Stillwell & Clarke (2004)
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GIS Tutorial II: Spatial Analysis Workbook, by David W. Allen (2009)
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An Introduction to Geographical Information Systems, by Heywood et al. (2nd Ed., 2002)
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Principles of Geographical Information Systems, by Burrough & McDonnell (1998)
“Stay afraid, but do it anyway. What’s important is the action. You don’t have to wait to be confident. Just do it and eventually the confidence will follow.” - Carrie Fisher
- Lecturer: Roxanne Murangi
Theory and practice relating to advanced geospatial analysis, including
· Raster data structures and algorithms for raster information management, extraction and analysis
· Vector data structure and algorithms for vector information management and analysis
· Raster and vector classification measurement and retrieval functions
· Raster and vector connectivity functions
· Raster and vector neighbourhood functions- Geometric, visibility, hydrological, network, environmental and cost/distance analysis, Triangulated irregular networks, digital elevation models and digital terrain models
· Raster and vector overlay functions
- Lecturer: Kaleb Negussie

Enrollment Key: MANUTD
- Lecturer: RYAN BENADE
- Lecturer: Ryan Benade
- Lecturer: Roxanne Murangi