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UndergraduateCode: BDS

Bachelor of Data Science

Duration

4 Years

Mode of study

Online

Academic overview

The Bachelor of Data Science programme is designed to facilitate learners with the knowledge, skills and attitudes necessary to address requirements and problems requiring Data Science expertise and to advise businesses, industry, academic institutions and government organs on planning and making smart, well-informed investments. The emerging tools and trends in Big Data analysis and Artificial Intelligence continuously inform curriculum development, implementation and knowledge dissemination within the philosophy of openness and breaking down boundaries and barriers to learning in all their forms. Data science skills qualify one to work as a data scientist within a wide array of fields, from investigative journalism where the learner can analyse data to find stories, to financial modelling, financial fraud prediction, urban planning, forensics, agriculture, social media analysis, remote sensing, international development, speech recognition, cybersecurity and many others. The programme is rigorous and designed to train high quality graduates with requisite professional and technical skills to effectively handle problems of data science, equipping learners with knowledge and skills on big data analytics, data mining, computational intelligence, machine learning, statistical learning, algorithms at scale and large scale databases optimisation.

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

Explore how your previous studies or professional experience can be credited towards this qualification through our RPL framework.

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

10%Online Self-Assessment -15%
20%Test (Online Open-Book Examination)
15%Project/Practical Work -20%
50%End of Course Examination

.

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

- Data Scientist - Data Analyst - Machine Learning Scientist - Machine Learning Engineer - Business Intelligence Scientist - Market Research Analyst

Application hub

Typical duration

4 Years

Delivery mode

Online

Fees

KES 79,000 / Year

≈ USD 669+10% Intl.

View full fee structure

Accreditation info

Fully accredited by the Commission for University Education (CUE) and recognised globally for digital-first excellence.

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