NUST eLearning
Search results: 1575
- Lecturer: Adeltraud Mughongora

This course is designed to provide students with deepened knowledge of mobile technology, as well as constraints and techniques essential in designing and developing mobile applications.
- Lecturer: WILBARD LAZARUS
- Lecturer: Dr Simon Muchinenyika
- Lecturer: Josephina Muntuumo
- Lecturer: Prof Dharm Singh
- Lecturer: Dr Munyaradzi Maravanyika
- Lecturer: Dr Titus Nghipulile
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- Lecturer: Dylan Bezuidenhout
- Lecturer: Dr Vaino Indongo
- Lecturer: Shapopi Kamanja
- Lecturer: Vanessa Tjijenda
- Lecturer: Linda Kambonde
- Lecturer: Mally Likukela
- Lecturer: Precious Mwikanda
The course is designed to enable students to apply the general principles, procedures and functions of various aspects of mortgage bonds, certificates of title, a notary public and notarial documents, including leases and the ante-nuptial contract.
- Lecturer: Sam Mwando
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- Lecturer: Prof Samuel Akinsola

This course is designed to expose students to Hypertext Markup Language (HTML) relevant to creating a personal web page and to maintain an electronic publication. Different uses of multimedia will be discussed, as well as the impact of growing online publishing on traditional media industries and commerce. Aspects of user-friendliness, design and content are covered. Students will create their own websites, which will be exhibited on the departmental website. Students must also participate in the production of an online publication by producing online articles.
- Lecturer: Peter Gallert
- Lecturer: Dr Emelda Gawas
- Lecturer: Immanuel Kandjabanga
- Lecturer: Johnson Mutirua
- Lecturer: Beatrice Mutonga
- Lecturer: Prof Phillip Santos

This course is designed to expose students to Hypertext Markup Language (HTML) relevant to creating a personal web page and to maintain an electronic publication. Different uses of multimedia will be discussed, as well as the impact of growing online publishing on traditional media industries and commerce. Aspects of user-friendliness, design and content are covered. Students will create their own websites, which will be exhibited on the departmental website. Students must also participate in the production of an online publication by producing online articles.
- Lecturer: Jordaania Kondjeni Andima
- Lecturer: Peter Gallert

- Lecturer: Ericky Iipumbu
- Lecturer: Isaac Nhamu

Welcome to the Multivariate Analysis course! This is an exciting journey where we will learn different Multivariate Analysis techniques. I work hard to ensure that your learning experience is as positive for you as possible. Your active participation in the course activities is also critical, and I hope you enjoy engaging with me during the rest of this semester.
This course is designed to broaden and enrich the student's knowledge and understanding of statistical methodology as it pertains to the study of multivariate techniques, equip students with skills in computing multivariate methods, and motivate them to apply the multivariate methods to solve real-life problems. In this course, a student will be taken through an Introduction; review of matrix algebra; Inference about a Multivariate Mean Vector; Inference about mean vector; Hypothesis testing on mean vector; Multivariate analysis of Variance; Multivariate techniques: Principal Components analysis; Factor analysis.
- Lecturer: Prof Dibaba Gemechu
- Lecturer: Elizabeth Kambwale
- Lecturer: Prof Max Mhene
- Lecturer: Naftali Indongo
- Lecturer: Kasnath Jazuvirua Kavezeri