Technology

Bachelor of Science in Data Science

The Bachelor of Science in Data Science is a cutting-edge programme that provides comprehensive training in data analysis, machine learning and statistical modelling. Offered at Strathmore University, JKUAT, Dedan Kimathi University of Technology and other select institutions, the programme prepares graduates for careers in data science, analytics and business intelligence.

The curriculum covers programming, statistics, probability, data structures, machine learning, data visualisation, big data analytics, database management, data mining, predictive analytics, natural language processing, business intelligence, Python, R, SQL, cloud platforms, research methods and a final year project. Students develop programming, statistical and analytical skills for data-driven decision making.

Kenya's data-driven economy, fintech growth and the demand for data professionals create strong demand for data science graduates. The programme is offered through lectures, programming labs, data analysis projects, hackathons and industrial attachment.

Graduates are prepared for careers as data scientists, data analysts, machine learning engineers, business intelligence analysts, data engineers, analytics consultants, research data analysts and AI specialists. They work in tech companies, banks, insurance, telecommunications, consulting firms, research institutions, government and startups.

The programme is accredited by the Commission for University Education (CUE). Admission requires KCSE mean grade C+ with B- in Mathematics and C+ in Physics or Chemistry. KUCCPS Cluster 3.

Prospective students should have strong analytical skills, a commitment to continuous learning, and an interest in contributing to Kenya's socio-economic development. The programme provides a solid foundation for further postgraduate study and professional advancement in related fields.

Duration: 4 years
Public, up to: Ksh 306,000
Private, up to: Ksh 270,030
Job market: High

The programme

What you study, how long it takes, and how it is delivered.

Practicalities

Study mode: Full-time
Attachment: 3 months
Average class: 30 students
Award: Bachelor

What you study

10 subjects

Programming
Statistics
Machine Learning
Data Visualisation
Big Data Analytics
Database Management
Data Mining
Predictive Analytics
Business Intelligence
Python and R

Modules

10 in the programme

Programming for Data Science
Year 1Semester 13 creditsCore
Python and R programming. The module covers theoretical foundations, practical applications and industry-relevant skills, assessed through continuous assessment tests, coursework and end-of-semeste...
Statistics
Year 1Semester 23 creditsCore
Statistical methods. The module covers theoretical foundations, practical applications and industry-relevant skills, assessed through continuous assessment tests, coursework and end-of-semester exa...
Machine Learning
Year 1Semester 33 creditsCore
ML algorithms. The module covers theoretical foundations, practical applications and industry-relevant skills, assessed through continuous assessment tests, coursework and end-of-semester examinati...
Data Visualisation
Year 2Semester 13 creditsCore
Visual analytics. The module covers theoretical foundations, practical applications and industry-relevant skills, assessed through continuous assessment tests, coursework and end-of-semester examin...
Big Data Analytics
Year 2Semester 23 creditsCore
Large-scale data processing. The module covers theoretical foundations, practical applications and industry-relevant skills, assessed through continuous assessment tests, coursework and end-of-seme...
Database Management
Year 2Semester 33 creditsCore
SQL and NoSQL databases. The module covers theoretical foundations, practical applications and industry-relevant skills, assessed through continuous assessment tests, coursework and end-of-semester...
Data Mining
Year 3Semester 13 creditsCore
Knowledge discovery. The module covers theoretical foundations, practical applications and industry-relevant skills, assessed through continuous assessment tests, coursework and end-of-semester exa...
Predictive Analytics
Year 3Semester 23 creditsCore
Forecasting models. The module covers theoretical foundations, practical applications and industry-relevant skills, assessed through continuous assessment tests, coursework and end-of-semester exam...
Business Intelligence
Year 3Semester 33 creditsCore
BI tools and dashboards. The module covers theoretical foundations, practical applications and industry-relevant skills, assessed through continuous assessment tests, coursework and end-of-semester...
Final Year Project
Year 4Semester 16 creditsCore
Capstone data science project. The module covers theoretical foundations, practical applications and industry-relevant skills, assessed through continuous assessment tests, coursework and end-of-se...

Specialisations

Data Visualisation
Visual analytics. This specialisation equips graduates with discipline-specific competencies for professional practice in Kenya and the East African region, with pathways to postgraduate study and professional certification.
Machine Learning
ML and AI. This specialisation equips graduates with discipline-specific competencies for professional practice in Kenya and the East African region, with pathways to postgraduate study and professional certification.
Big Data Engineering
Data infrastructure. This specialisation equips graduates with discipline-specific competencies for professional practice in Kenya and the East African region, with pathways to postgraduate study and professional certification.
Business Analytics
Business intelligence. This specialisation equips graduates with discipline-specific competencies for professional practice in Kenya and the East African region, with pathways to postgraduate study and professional certification.

A day as a student

A typical day involves attending data science lectures, programming in Python and R, building machine learning models, creating data visualisations, working with databases, analysing real datasets, participating in data hackathons, and developing analytics projects.

The trade offs

In its favour

One of the most in-demand skills globally
Excellent earning potential
Opportunities across all industries

Against it

Requires strong mathematics and programming skills
Rapidly evolving field requiring continuous learning
Limited number of universities offering the programme

What it costs

Tuition at both ends of the market, and how to pay for it.

What it costs, and where

Against 191 technology courses

Public184k to 306k

184k at Meru University of Science and Technology306k at Co-operative University of Kenya

Private219k to 270k

219k at Kabarak University270k at KCA University

Annual tuition in Kenyan shillings, rounded. The upright tick is the median for this field, so a bar sitting entirely to its right is an expensive programme by the standards of its own subject.

The fine print

KUCCPS: Meru 184K, Co-op 306K. Kabarak 219K, KCA 270K. educationnewshub.co.ke, kcau.ac.ke

HELB loans and government scholarships under the new funding model are available. Tech companies may offer sponsorships.

Funding options

HELB Loan
County Bursaries
Government Scholarship (New Funding Model)

Scholarships

5 recorded

Huawei Seeds for the Future Kenya
Scholarship
Talented ICT/STEM university students with a GPA of 3.0+
Generation Google Scholarship
Scholarship
Women in computer science and related technical fields
Higher Education Fund (HEF)
ScholarshipKsh 200,000Kenyan
KUCCPS-placed students
Higher Education Loans Board (HELB) Loan
LoanKsh 80,000Kenyan
Kenyan undergraduate students
County Government Bursaries
BursaryKsh 50,000Kenyan
Kenyan students from participating counties

Getting in

The grades, the alternatives, and who accredits the award.

What you need

KCSE mean grade: C+
Alternative entry: KCSE mean grade C+ with B- in Mathematics and C+ in Physics or Chemistry. Diploma in computer science, IT, statistics or related field from a recognised institution. KUCCPS Cluster 3.

Mathematics
B-
Physics or Chemistry
C+
English or Kiswahili
C+

How you are assessed

4 components

Continuous Assessment Tests
Cat20% of the mark
Regular tests and assignments
Data Analysis Projects
Practicum30% of the mark
Hands-on data projects
End of Semester Examinations
Written examination40% of the mark
End of semester written exams
Final Year Project
Project10% of the mark
Capstone data science project

Accreditation

Accredited by the Commission for University Education (CUE). Offered at Strathmore, JKUAT, DeKUT and other select institutions. Admission requires KCSE mean grade C+ with B- in Mathematics and C+ in Physics or Chemistry. KUCCPS Cluster 3.

Accredited by

Commission for University Education
AcademicRequired
Statutory body responsible for accreditation of university programmes in Kenya

Where it leads

The roles it opens, and what you leave with.

Where graduates go

5 roles

Data Engineer
Moderate demandKsh 180,000 to Ksh 500,000
Data infrastructure
Machine Learning Engineer
High demandKsh 200,000 to Ksh 550,000
ML engineering
Business Intelligence Analyst
High demandKsh 150,000 to Ksh 380,000
BI and analytics
Data Scientist
High demandKsh 200,000 to Ksh 600,000
Data science and ML
Data Analyst
High demandKsh 150,000 to Ksh 400,000
Data analysis

Graduate outcomes

Graduates pursue careers as data scientists, data analysts and machine learning engineers in tech companies, banks, telecommunications and consulting firms.

Where these fields lead

8 careers

Tools you will learn

Python
ProgrammingPrimary
Primary programming language for data science
R
Statistical computingPrimary
Statistical analysis and data visualization
SQL
Database
Database querying for data extraction
Tableau
Data visualization
Data visualization and business intelligence
Jupyter Notebook
Development
Interactive notebooks for data analysis
Git/GitHub
Version control
Version control for data science projects

Certifications

Industry links

Common misconceptions

Data science is just about statistics.
The programme covers programming, machine learning, big data, visualisation and business intelligence.
Data science is only for tech companies.
Every sector needs data professionals, from healthcare to finance to government.
You need a PhD to be a data scientist.
A bachelor's degree with strong skills is sufficient for most data science roles.
Data science is just a buzzword.
Data science drives decision making in virtually every industry.