Overview
Philosophy of the Programme
The philosophy of the Master of Science in Artificial Intelligence is to inspire students who are technically skilled and socially conscious to take a leading role in the responsible exploitation of the capabilities of artificial intelligence to tackle complex challenges across various sectors of the economy.
This aligns with the university's philosophy of inspiring and connecting with the Kenyan community, providing leadership and stewardship, and fostering confidence that society can achieve sustainable development guided by the values of excellence, innovation, moral responsibility, and patriotism.
Why Choose the MSc in AI? Our MSc in Artificial Intelligence was designed after a comprehensive needs assessment to ensure graduates are prepared for the real demands of today’s AI landscape. Employers, alumni, students, and policymakers all contributed insights, helping us shape a program that blends cutting‑edge theory with practical application. The curriculum is aligned with national strategies, industry requirements, and global trends, giving you the skills to thrive in diverse sectors.
What Makes This Program Unique? You will gain hands‑on experience with real‑world case studies, learn to provide AI solutions in an industry practically, and explore ethical and societal implications of AI. Employers have emphasized the need for graduates who can bridge theory and practice, while policymakers highlighted human capital development. With interdisciplinary training and a focus on AI tools, skills and research, this program equips you to become not just an AI expert, but a leader driving innovation and responsible AI growth.
Summary of Learning Outcomes Graduates of the MSc in Artificial Intelligence will demonstrate mastery of foundational AI concepts, methods, and practical applications. They will be able to design and implement suitable algorithms and tools to address challenges in computing, industry, and society.
Students will also gain the ability to critically evaluate AI systems in terms of performance, ethics, and responsible use, while contributing new knowledge and innovative solutions through rigorous, action‑oriented research that addresses real societal needs.
Contacts
Department of Computing & Informatics, Chiromo Campus
Structure
MODE OF DELIVERY
Face-to-Face Mode
This will comprise lectures, laboratory, seminars, tutorials, assignments, presentations, problem-based learning, self-directed learning, and group discussions.
Open Distance and e-Learning Mode
This will be offered using a multi-media approach, including self-instructional print and electronic study materials.
Blended Learning Mode
This will combine online learning with synchronous, asynchronous, and face-to-face methods. This shall apply to relevant course units.
Intake - September
Duration and Structure of Courses
- The programme shall take a minimum of four semesters (two academic years) and a maximum of twelve semesters (four academic years), each fifteen weeks long.
- The programme shall be offered by coursework, examination, practicum, and a research project.
- The programme shall consist of nine taught course units, the practicum, and the research project.
- A course unit shall be defined as 60 contact hours comprising lectures, seminars, self-study, tutorials, and practical sessions.
- A candidate shall successfully complete nine course units, a practicum, and a research project.
- The research project shall be equivalent to three course units.
- A candidate who fails to successfully complete the programme within the maximum allowable duration of twelve semesters shall, at the recommendation of the examiners' committee and approval by the Senate, be discontinued from the program
COURSE UNITS OFFERED
Year 1 Semester 1
SMA6151 Mathematics for AI 1
SMA6153 Mathematics for AI 2
SCS6155 Advanced Machine Learning
SCS6157 Deep Learning
Semester 2
SCS6152 Research Methodology and AI Ethics
SCS6154 Big Data Analytics and Automation
SCS6156 Emerging AI Topics
Electives (Choose two)
Year 2 Semester 3
SCS6257 Practicum
SCS6259 AI Research Project
Semester 4
SCS6259 AI Research Project
Electives 1 (Choose two)
SCS6160 Computer Vision and Imaging
SCS6162 Advanced Natural Language Processing
SCS6164 Generative Artificial Intelligence
SCS6166 Robotics
Admission Requirements
ADMISSION REQUIREMENTS
Minimum Admission Requirements
The common regulations for Masters Degrees in the University of Nairobi shall apply.
The following shall be eligible for admission into the Master of Science in Artificial
Intelligence:
- Holders of a Bachelor’s degree in any discipline of the University of Nairobi of at
least Upper Second Class Honours, of the University of Nairobi, or equivalent
qualification from an institution recognized by the Senate. - Holders of a Bachelor’s degree in any discipline of the University of Nairobi of
Lower Second Class Honours, of the University of Nairobi, or equivalent
qualification from an institution recognized by the Senate. In addition, they must
have demonstrable relevant industry experience of at least two years. - Applicants shall also be required to pass a department-based entrance examination. The entrance exams will require that all applicants show evidence of either industrial practice or undergraduate-level knowledge in any of the following computer science areas:
Programming, Data Structures and Algorithms, and Mathematics (Calculus, Probability and Statistics, Linear Algebra) obtained from and certified by an internationally recognized certification body. The list of such recognized institutions can be obtained from the Department of Computer Science. - Proficiency in the use of the English language will be required. This will be evaluated during the department-based entrance exams for students whose mode of instruction in Previous levels of study was not in English.
Credit Transfer and Exemption
- The common regulations governing credit transfers and exemptions of the University of Nairobi shall apply.
- A candidate seeking course exemptions shall apply in writing to the Academic Registrar
through the Dean of the Faculty and Chairman of the Department of Computing and Informatics, justifying the request and attaching certified supporting testimonials and evidence of having paid the relevant fee as prescribed by the university. - The course(s) to be exempted must have been taken and passed at the graduate level in a university recognized by the university senate. It shall have matching content and contact hours similar to which credit transfer is being sought.
- Evidence of course content and contact hours for the course earlier done and passed shall be included in the application for exemption.
- A candidate shall only be exempted from courses in the first year of study and not more than one-third (1/3) of the total number of courses taken in the programme.
- The candidate seeking course exemption shall meet all the University of Nairobi
prescribed costs relevant to the exemptions.
Careers
Industry-Common AI Applications
Healthcare: Diagnostic imaging, drug discovery, patient monitoring, operational efficiency Clinical AI Engineer, Medical Imaging Specialist
Finance & Insurance: Fraud detection, risk modeling, algorithmic trading, compliance, personalized advice AI Risk Modeler, Fraud Detection ML Engineer, Quantitative Analyst
Technology & SaaS: Building copilots, search assistants, recommendation engines, cloud AI services AI Product Engineer (LLMs), AI Solutions Architect
Manufacturing & Logistics: Predictive maintenance, quality control, supply chain optimization, robotics automation Robotics Engineer, AI Platform Architect
Retail & E-commerce: Personalizing marketing, optimizing supply chains, enhancing customer experience AI Strategy and Innovation Manager, Business Analyst
Fees and Funding
Fee Structure
|
SN |
ITEM |
AMOUNT (KES) |
TOTAL |
||
|
SEM 1 |
SEM 2 |
SEM 3 |
|||
|
YEAR 1 |
|||||
|
1. |
Tuition - 9 Units |
240,000 |
300,000 |
540,000 |
|
|
2. |
Project Supervision |
48,000 |
48,000 |
||
|
3. |
Department of Computing Lab |
15,000 |
15,000 |
15,000 |
45,000 |
|
4. |
ICT Services - (Per Year) |
7,000 |
0 |
7,000 |
|
|
5. |
Examination (Per Unit @1000) |
5,000 |
5,000 |
10,000 |
|
|
6. |
Registration (Per Semester@2250) |
2,250 |
2,250 |
2,250 |
6,750 |
|
7. |
Medical Fee (Per Year) |
6,500 |
0 |
6,500 |
|
|
8. |
Activity- (Per Year) |
2,000 |
0 |
2,000 |
|
|
9. |
ID Card (Per Year) |
1,000 |
0 |
1,000 |
|
|
10. |
Caution - (Once) |
5,000 |
0 |
5,000 |
|
|
11. |
Library (Per Year) |
5,000 |
0 |
5,000 |
|
|
12. |
Student Organisation (Per Year) |
1,000 |
0 |
1,000 |
|
|
TOTAL |
289,750 |
322,821 |
65,250 |
677,250 |
|
|
YEAR 2 |
SEM 1 |
||||
|
13. |
Project Supervision |
48,000 |
48,000 |
||
|
14. |
Department of Computing Lab |
15,000 |
15,000 |
||
|
15. |
ICT Services - (Per Year) |
7,000 |
7,000 |
||
|
16. |
Registration (Per Semester@2250) |
2,250 |
2,250 |
||
|
17. |
Examination (Per Unit @1000) |
5,000 |
5,000 |
||
|
18. |
Medical Fee (Per Year) |
6,500 |
6,500 |
||
|
19. |
Activity- (Per Year) |
2,000 |
2,000 |
||
|
20. |
ID Card (Per Year) |
1,000 |
1,000 |
||
|
21. |
Library (Per Year) |
5,000 |
5,000 |
||
|
22. |
Student Organization (Per Year) |
1,000 |
1,000 |
||
|
TOTAL |
92,750 |
92,750 |
|||
|
GRAND TOTALS |
770,000 |
||||
Exam Regulations
STUDENT ASSESSMENT CRITERIA
- The course will be assessed through:
Formative assessment, which shall consist of:
- Continuous assessment tests such as sit-in quizzes in a controlled environment;
- Practical assignments where students will develop programs or other types of
solutions to problems assigned by the lecturer; - Oral presentation where students will show their mastery of the topic examined;
- Seminars where students will make presentations in the presence of other
students; - Group work, which will consist of the assignment of tasks to be completed by two or more students.
- Summative assessment
This will consist of the end-of-semester sit-in exam that will be done in a controlled environment.
- Practicum
This will consist of placement of the student in industry or an appropriate
organization such as a research lab or hospital. The student will be assessed using their practicum journal, practicum report, and a technical paper - Research Project
The project will be assessed by the students presenting their work to a panel.
Additionally, the student project report will also be assessed and contribute to their final score.
- GRADING SYSTEM
The final grading of the individual course units shall be as follows:
70 – 100% A
60 – <70% B
50 – <60% C
Below 50% Fail - EXAMINATION REGULATIONS
Coursework Examination: All taught course units shall be examined at the end of the respective semesters.
a). Candidates shall take either the sit-in, oral, or online exams in accordance with the
applicable university examination policy and guidelines.
b). Satisfactory completion of all requisite coursework (assignments, laboratories,
practicals and continuous assessment tests) shall be a condition of admission to the examination at the end of the respective semester.
c). A written examination for a course unit shall have a duration of two hours.
Each course unit or its equivalent shall be marked independently out of a maximum of
100 marks, and the pass mark shall be 50%.
d). The complete assessment of a taught unit shall consist of coursework and an
examination. The contribution towards the unit aggregate shall be 50% for coursework.
and 50% for the examination.
e). A candidate who fails to satisfy the examiners in any unit may, on the recommendation of the Board of Examiners and approval by the Senate, be allowed to sit for supplementary examinations in the failed unit(s) when scheduled.
f). A candidate who fails to satisfy the examiners in any supplementary exam will, on the recommendation of the Board of Examiners and approval by the Senate, be required to retake the failed unit(s).
g). A pass obtained in any supplementary examination will be recorded as 50% in the candidate's academic record.
h). A candidate shall be required to pass in all the taught course units before being allowed to undertake the research project.
- A candidate who:
- Has failed any course unit or its equivalent after four attempts (including
supplementaries and retakes) or has failed to take any prescribed examination without good cause or fails to complete the programme within the maximum period shall, on the recommendation of the Faculty Board of Examiners and approval by the Senate, be discontinued from the program. - Examination irregularities and malpractices shall be handled according to the University of Nairobi’s Procedure for Examination Disciplinary (UON/OP/14).
