Technology

Bachelor of Science in Data Science and Analytics

This Bachelor's programme prepares students for professional careers in data science and analytics. It develops expertise in statistical analysis, data mining, business intelligence, and predictive analytics while building practical skills for analysing data and supporting data-driven decision-making.

Students analyse data, develop analytics models, implement data mining techniques, create business intelligence solutions, visualise data, evaluate analytics performance, assess data quality, and communicate insights. They also strengthen statistical analysis, programming skills, problem-solving, data storytelling, and analytical thinking.

Kenya's data-driven economy requires professionals who can analyse data, develop analytics solutions, and support decision-making across fintech, banking, insurance, telecommunications, and government agencies.

The programme combines coursework, analytics laboratories, business intelligence projects, industrial attachment, and data analysis projects to build comprehensive data science and analytics expertise.

Graduates pursue careers as data analysts, business intelligence analysts, data scientists, analytics consultants, and reporting specialists across banks, insurance companies, fintech firms, and government agencies.

The programme is ideal for students interested in data analysis, business intelligence, statistics, programming, and extracting insights from data for business decision-making. The programme emphasises practical skills through laboratory sessions, industrial attachments, and project-based learning that prepare graduates for real-world data challenges across multiple sectors.

Duration: 4 years
Public, up to: Ksh 224,400
Private, up to: Ksh 441,500
Job market: High

The programme

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

Practicalities

Study mode: Full-time
Attachment: 6 months
Average class: 50 students
Award: Bachelor

What you study

10 subjects

Statistics and Statistical Analysis
Data Mining and Data Analytics
Business Intelligence and Analytics
Predictive Analytics and Forecasting
Programming for Analytics
Database Management and Data Warehousing
Data Visualisation and Reporting
Machine Learning for Analytics
Big Data Analytics
Research Methods and Analytics Research

Modules

10 in the programme

Statistics and Statistical Analysis
Year 1Semester 13 creditsCore
Statistics and Statistical Analysis: Statistics, statistical analysis, probability, and supporting statistics. Includes probability theory, hypothesis testing, regression analysis, and data interpr...
Data Mining and Data Analytics
Year 1Semester 23 creditsCore
Data Mining and Data Analytics: Data mining, data analytics, data analysis, and supporting data mining. Covers data modelling, query optimisation, storage structures, and information retrieval.
Business Intelligence and Analytics
Year 1Semester 33 creditsCore
Business intelligence, analytics, reporting, and supporting business intelligence.
Predictive Analytics and Forecasting
Year 2Semester 13 creditsCore
Predictive analytics, forecasting, predictive modelling, and supporting predictive analytics.
Programming for Analytics
Year 2Semester 23 creditsCore
Programming for Analytics: Programming for analytics, Python, R, and supporting programming. Includes practical programming exercises, algorithm design, and system implementation.
Database Management and Data Warehousing
Year 2Semester 33 creditsCore
Database Management and Data Warehousing: Database management, data warehousing, SQL, and supporting database management. Covers planning, organising, leadership, and control in organisational cont...
Data Visualisation and Reporting
Year 3Semester 13 creditsCore
Data Visualisation and Reporting: Data visualisation, reporting, dashboards, and supporting data visualisation. Covers data modelling, query optimisation, storage structures, and information retrie...
Machine Learning for Analytics
Year 3Semester 23 creditsCore
Machine learning for analytics, ML algorithms, predictive modelling, and supporting machine learning.
Big Data Analytics
Year 3Semester 33 creditsCore
Big data analytics, big data technologies, data processing, and supporting big data analytics.
Research Methods, Analytics Research and Project
Year 4Semester 16 creditsCore
Research methods, data collection, monitoring and evaluation, M and E, analytics research, research project, and supporting research methods and project work.

Specialisations

Business Intelligence and Analytics
Focuses on business intelligence, analytics, reporting, and dashboards. 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.
Data Analytics and Data Mining
Specialises in data analytics, data mining, data analysis, and data insights. 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.
Financial Analytics and Risk Analytics
Focuses on financial analytics, risk analytics, financial modelling, and risk assessment. 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 Analytics
Focuses on big data analytics, big data technologies, data processing, and data engineering. 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.
Predictive Analytics and Forecasting
Concentrates on predictive analytics, forecasting, predictive modelling, and forecasting models. 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 starts with morning lectures on statistics, data analytics, or business intelligence, followed by analytics laboratories, BI projects, or industry visits. Students analyse data, develop analytics models, work with BI tools, visualise insights, and work on their analytics projects. Industrial attachments at banks, insurance companies, and fintech firms provide hands-on experience.

The trade offs

In its favour

High demand — data-driven economy, fintech growth, and digital transformation create strong demand for analytics professionals.
Diverse applications — graduates work in banking, insurance, fintech, telecommunications, government, and various industries.
Business impact — analytics professionals directly support business decision-making and strategic planning.

Against it

Continuous learning — analytics faces rapid technology changes, continuous learning requirements, and skills obsolescence.
Technical complexity — analytics requires strong technical skills in statistics, programming, and data analysis.
Sedentary work — analytics involves long hours of coding, screen time, and sedentary work patterns.

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

Public224k to 224k

224k at Jomo Kenyatta University of Agriculture and Technology224k at Jomo Kenyatta University of Agriculture and Technology

Private219k to 442k

219k at Kabarak University442k at United States International University Africa

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

JKUAT 224K (KUCCPS). Kabarak 219K, USIU 442K. educationnewshub.co.ke, usiu.ac.ke

Students can access HELB undergraduate loans and KUCCPS placement. County bursaries, analytics industry sponsorships, and international data science scholarships are available.

Funding options

HELB Undergraduate Loan
KUCCPS Placement
County Government Bursaries

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 Loans Board (HELB) Loan
LoanKsh 60,000Kenyan
Kenyan citizens pursuing undergraduate studies at accredited universities.
County Government Bursaries
BursaryKsh 50,000Kenyan
Students from specific counties. Varies by county.
Analytics Industry Sponsorships
ScholarshipKsh 150,000Kenyan
Banks, insurance companies, and fintech organisations may sponsor analytics students in exchange for service commitment.

Getting in

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

What you need

KCSE mean grade: C+
Alternative entry: Diploma in Information Technology, Computer Science, Statistics, Mathematics, or related fields from recognised institutions may be considered for upgrading. Relevant programming or data analysis experience is advantageous.

Mathematics
C+
Physics or Computer Studies
C
English or Kiswahili
C
Chemistry or Biology
C

How you are assessed

5 components

Research Project
Research10% of the mark
Independent analytics research project, assessed through written report and presentation.
End of Semester Written Examinations
Exam30% of the mark
Written examinations covering data science, analytics, business intelligence, and analytics research.
Continuous Assessment Tests and Assignments
Cat20% of the mark
Assignments, tests, presentations, case studies, and analytics projects throughout each semester.
Data Science and Analytics Practical Examinations
Practicum30% of the mark
Assessment of analytics competencies including data analysis, business intelligence, data visualisation, and predictive analytics.
Industry Attachment Assessment
Clinical10% of the mark
Assessment of industry attachments including analytics work, BI work, documentation, and supervision evaluation.

Accreditation

Accredited by the Commission for University Education (CUE). Certified by Communication Authority of Kenya (CAK) for ICT professionals. The Kenya Information and Communications Act governs ICT. The National ICT Policy guides digital development. Data Protection Act governs data protection.

Accredited by

Commission for University Education
NationalRequired
CUE accredits all university programmes in Kenya.

Where it leads

The roles it opens, and what you leave with.

Where graduates go

5 roles

Data Analyst / Analytics Analyst
High demandKsh 65,000 to Ksh 160,000
Analyses data, develops insights, analytics solutions, and supports data analysis at banks, insurance companies, or fintech firms.
Reporting Analyst / Reporting Specialist
High demandKsh 60,000 to Ksh 140,000
Develops reports, reporting solutions, data reporting, and supports reporting at banks, insurance companies, or government agencies.
Predictive Analytics Specialist / Forecasting Analyst
High demandKsh 70,000 to Ksh 160,000
Develops predictive analytics, forecasting models, predictive modelling, and supports forecasting at banks, insurance companies, or fintech firms.
Data Scientist / Analytics Consultant
High demandKsh 75,000 to Ksh 170,000
Develops data science solutions, analytics consulting, predictive models, and supports analytics at consulting firms, banks, or fintech companies.
Business Intelligence Analyst / BI Analyst
High demandKsh 65,000 to Ksh 150,000
Develops business intelligence, reporting, dashboards, and supports decision-making at banks, insurance companies, or government agencies.

Graduate outcomes

Graduates work as data analysts and business intelligence analysts. Data science and analytics is in high demand driven by data-driven decision-making. Salaries range from KES 65,000 to 160,000 per month. Ministry of ICT, KNBS, banks, and insurance companies offer the main opportunities.

Where these fields lead

8 careers

Tools you will learn

GitHub Copilot
Ai
VS Code
Code
Docker
Cloud
Git
CodePrimary
PostgreSQL
Database
Python
CodePrimary

Certifications

Industry links

Common misconceptions

Data science and analytics is just about programming.
Data science and analytics includes statistics, data mining, business intelligence, predictive analytics, and data visualisation — programming is one component.
Data science and analytics is only for technology companies.
Data science and analytics applies to banks, insurance companies, fintech, telecommunications, government agencies, and many other industries beyond technology companies.
There are limited career opportunities for analytics graduates in Kenya.
Kenya's data-driven economy, fintech growth, banking analytics needs, insurance data requirements, and digital transformation create demand for analytics professionals at banks, insurance companies, and fintech firms.
This programme has limited career opportunities.
Graduates pursue diverse career paths across multiple sectors in Kenya and internationally.