Bachelor of Data Science
Join a world-class institutional environment designed for the digital age. This programme offers a direct pathway to global career outcomes through technology-enabled learning.
Academic overview
Expected outcomes
- Describe the applications of data science in a wide range of data-related fields.
- Analyse and adapt the latest data science technologies to solve real-world problems in a broad range of sectors.
- Formulate appropriate models of data analysis and undertake a project in an independent or collaborative environment.
- Exhibit an in-depth understanding of the codes of ethics and conduct of data science professions.
Entry requirements
- Satisfy the general University admission criteria for undergraduate programmes.
- A mean grade of C+ and above at KCSE or its equivalent. In addition, a candidate must have a minimum grade of C+ or its equivalent in the following subjects: Mathematics, (physics or chemistry or biology) and a language.
- A holder of a diploma or professional qualification in the areas of computer science or their equivalents.
- KCSE certificate or equivalent and a certificate of foundation or bridging courses from recognised institutions.
- Kenya Advanced Certificate of Education with a minimum of 1 principal and subsidiary passes.
- Recognition of prior learning, including workplace training of 2 years, work experience in a relevant field of 2 years, or two short courses lasting at least 3 months each in relevant fields, as determined by Senate.
Credit and Entry pathways
Programme structure
The programme runs over four academic years, each comprising two semesters, for a total of 8 semesters. The minimum total courses for the programme are 48 and the minimum total course credit hours required for graduation is 168. Each course carries 3 credit hours, with one credit hour equivalent to a minimum of 13 instructional hours. A typical course comprises 13 hours of asynchronous online lectures, 26 hours of synchronous tutorials/group work, 39 hours of individualised learning and 6 hours reserved for examinations, totalling 84 instructional hours per course. Field Attachment is conducted for at least eight (8) weeks at the end of the third year. Level one covers introductory topics in Data Science where learners take all core courses and two University Common Courses. Level two covers intermediate concepts, Level three covers advanced concepts, and Level four covers advanced concepts in areas of specialisation where students take all core courses.
Assessment methods
.
Project courses (DSC200 and DSC400) are assessed through Presentation (Report and Oral Presentation) 25%, e-Portfolios 25% and Rubric Based Project Report 50%.
The pass mark is 50% for each course.
Grading: A (80% to 100%), B (70% to <80%), C (60% to <70%), D (50% to <60%), E (below 50%, Fail).
Global careers
Application hub
Typical duration
Delivery mode
Online
Accreditation info
Fully accredited by the Commission for University Education (CUE) and recognised globally for digital-first excellence.
School of Science & Technology
Related programmes
Undergraduate
Bachelor of Science in Computer Science
Explore programmeUndergraduate
Bachelor of Science in Cybersecurity and Digital Forensics
Explore programmeUndergraduate
Bachelor of Science in Agritechnology and Food Systems
Explore programmePostgraduate