Technology

Diploma in Big Data

The Diploma in Big Data is a programme that equips students with knowledge and practical skills in big data technologies, data analytics and data-driven decision-making. Offered at Lukenya University, the programme combines foundational data science concepts with practical big data technology skills.

The curriculum covers data fundamentals, statistics, programming (Python and R), database management, SQL, data warehousing, big data ecosystems (Hadoop, Spark), data visualisation, machine learning basics, data mining, cloud computing, data security, business intelligence, data ethics, communication skills, ICT and entrepreneurship. Students develop both data analysis skills and big data technology competencies.

Kenya's technology sector is experiencing growing demand for data professionals who can manage, analyse and derive insights from large datasets. The programme responds to the need for entry-level data practitioners who can support data-driven operations in banks, telecom companies, government agencies, healthcare, agriculture and technology firms.

The programme is delivered through lectures, computer laboratory sessions, data analysis projects, case studies and industrial attachment. Students gain hands-on experience in data processing, visualisation, big data tools and analytics through laboratory sessions and practical projects using real-world datasets.

Graduates pursue careers as data analysts, data technicians, business intelligence assistants, database assistants, data entry supervisors, junior data scientists and analytics trainees in banks, telecom companies, government agencies, technology companies, research institutions and consulting firms. They can also progress to a Bachelor of Science in Data Science or related degree programmes.

Prospective students should have analytical skills, interest in data and technology, and basic mathematical aptitude. The programme is suitable for students seeking practical data skills for entry-level positions or further study.

Duration: 2 years
Public, up to: Ksh 81,335
Private, up to: Ksh 77,700
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: 25 students
Award: Diploma

What you study

8 subjects

Data Fundamentals and Statistics
Python and R Programming
Database Management and SQL
Big Data Ecosystems (Hadoop and Spark)
Data Visualisation and Business Intelligence
Machine Learning Basics and Data Mining
Cloud Computing and Data Security
Data Ethics and Entrepreneurship

Modules

8 in the programme

Data Fundamentals and Programming
Year 1Semester 13 creditsCore
Covers data fundamentals, statistics, Python programming, data structures, file handling and introductory data manipulation.
Database Management and SQL
Year 1Semester 13 creditsCore
Covers relational databases, database design, normalisation, SQL queries, stored procedures and database administration basics.
Data Warehousing and Big Data Ecosystems
Year 1Semester 23 creditsCore
Covers data warehousing concepts, ETL processes, Hadoop ecosystem, HDFS, MapReduce, Spark and distributed data processing.
Data Visualisation and Business Intelligence
Year 1Semester 23 creditsCore
Covers data visualisation principles, charts and dashboards, Tableau, Power BI, business intelligence concepts and reporting.
Machine Learning Basics and Data Mining
Year 2Semester 13 creditsCore
Covers machine learning concepts, supervised and unsupervised learning, classification, regression, clustering and data mining techniques.
Cloud Computing and Data Security
Year 2Semester 13 creditsCore
Covers cloud computing platforms, cloud data storage, data security, data privacy, data protection compliance and ethical data handling.
R Programming and Advanced Analytics
Year 2Semester 23 creditsCore
Covers R programming, statistical analysis, predictive analytics, time series analysis and advanced data manipulation techniques.
Industrial Attachment and Data Project
Year 2Semester 26 creditsCore
A three-month industrial attachment at a data-driven organisation, assessed through an attachment report and a practical data analytics project.

Specialisations

Data Analytics
Focuses on statistical analysis, data visualisation and business intelligence for careers as data analysts.
Big Data Engineering
Specialises in big data infrastructure, Hadoop, Spark and data pipelines for careers in data engineering.
Data Visualisation
Focuses on data visualisation, dashboard design and reporting for careers in business intelligence.
Machine Learning
Specialises in machine learning fundamentals, predictive modelling and data mining for careers in data science.

A day as a student

A typical day begins with a morning lecture on statistics or database management, followed by a computer laboratory session writing Python scripts for data analysis. Afternoon sessions may include a practical exercise on data visualisation using tools like Tableau or Power BI, a group project analysing a real-world dataset, or a tutorial on Hadoop or Spark for big data processing. Students also work on data mining assignments and machine learning exercises.

The trade offs

In its favour

Data skills are in high demand across Kenya's growing digital economy, with opportunities in banking, telecom, government and technology sectors.
The programme combines practical programming skills with data analytics, providing versatile competencies for the technology sector.
Graduates can progress to a Bachelor of Science in Data Science or Computer Science with credit transfers.

Against it

The programme is offered at only one university, limiting study location options.
The technology field evolves rapidly, requiring graduates to continuously update their skills beyond the diploma.

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

Public67k to 81k

67k at Kamukunji TVC81k at Kibabii University TVET

Private78k to 78k

78k at Zetech University78k at Zetech 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

Kamukunji TVC 67K, Kibabii 81K/yr pub. Zetech 77.7K/yr pvt (kamukunjitvc.ac.ke, kibu.ac.ke).

Students can access HELB loans. Lukenya University may offer internal financial aid for qualifying students.

Funding options

HELB Loan

Scholarships

1 recorded

HELB Loan
LoanKsh 40,000Kenyan
Kenyan students enrolled in accredited programmes at recognised institutions

Getting in

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

What you need

KCSE mean grade: C-
Alternative entry: Certificate in ICT, Data Science or related field from a recognised institution.

How you are assessed

4 components

Continuous Assessment Tests
Written examination30% of the mark
Mid-semester and end-of-semester written tests covering statistics, programming and database concepts.
Laboratory Practicals
Practicum40% of the mark
Assessment of computer laboratory sessions including Python programming, SQL queries and data visualisation exercises.
Data Analytics Project
Project50% of the mark
A practical data analytics project applying big data tools and techniques to a real-world dataset.
Industrial Attachment Report
Practicum100% of the mark
Assessment of performance during industrial attachment at a data-driven organisation.

Accreditation

Accredited by the Commission for University Education (CUE). The programme is offered at Lukenya University.

Accredited by

Commission for University Education
AcademicRequired
Accredited by the Commission for University Education (CUE). The programme is offered at Lukenya University.

Where it leads

The roles it opens, and what you leave with.

Where graduates go

4 roles

Data Analyst
High demandKsh 45,000 to Ksh 150,000
Collects, cleans, analyses and visualises data to support decision-making in organisations using statistical and visualisation tools.
Data Technician
Moderate demandKsh 35,000 to Ksh 100,000
Supports data operations including data entry, data cleaning, database maintenance, data processing and report generation.
Business Intelligence Assistant
Moderate demandKsh 40,000 to Ksh 120,000
Supports BI operations including dashboard creation, report generation, data querying and business performance analysis.
Database Assistant
Moderate demandKsh 38,000 to Ksh 110,000
Maintains databases, writes SQL queries, supports data backups, manages data access and assists with database administration.

Graduate outcomes

Graduates work as data analysts, data technicians and business intelligence assistants in banks, telecom companies, government agencies and technology firms.

Where these fields lead

8 careers

Tools you will learn

Python
CodePrimary
R
Code
Apache Hadoop
Tool
Apache Spark
Tool

Certifications

Commission for University Education (CUE) Accreditation

Industry links

Common misconceptions

Big data is only for mathematicians.
While statistics is important, the programme teaches data skills from fundamentals, making it accessible to students with basic mathematical aptitude and interest in technology.
You need a degree to work with data.
A diploma provides practical data skills for entry-level positions as data analysts and data technicians, with opportunities to progress to degree-level study.
Big data is just about large numbers.
Big data encompasses data collection, storage, processing, analysis, visualisation, security and ethics, requiring diverse technical and analytical skills.
There are no jobs for big data diploma graduates in Kenya.
Kenya's growing digital economy creates demand for data professionals in banking, telecom, government, healthcare, agriculture and technology sectors.