BSc Data Science & Artificial Intelligence
April 10, 2026 2026-04-13 9:14Bachelor of Science in Data Science & Artificial Intelligence
Reinvent the Future with Data & AI
In today’s data-driven world, Data Science and Artificial Intelligence are transforming industries, economies, and everyday life. From healthcare and finance to smart cities and autonomous systems, these technologies are shaping the future.
At Academic City, this programme equips students with the skills to analyse data, build intelligent systems, and develop AI-driven solutions that solve real-world problems.
Data Science & AI at ACity
The programme provides a strong foundation in mathematics, statistics, and computing, combined with hands-on experience in machine learning, data analytics, and AI system development.
Students will:
- Work with real-world datasets and AI tools
- Build predictive models and intelligent systems
- Develop software and AI applications
- Use modern technologies like Python, cloud platforms, and big data tools
- Apply ethical and responsible AI practices
Graduates are prepared to lead innovation in a rapidly evolving digital economy.
Top Careers in Data Science & AI
- Data Scientist
- Machine Learning Engineer
- AI Engineer
- NLP Engineer
- Data Analyst
- Business Intelligence Analyst
- Computer Vision Engineer
- AI Product Developer
Entry Requirements
Minimum C6 in 6 subjects including 3 core subjects (English, Mathematics, Integrated/General Science) and 3 elective subjects. (Physics, Elective Mathematics + Chemistry OR any other elective relevant to the chosen Program)
Minimum D or a pass in 6 subjects including 3 core subjects (English, Mathematics, Integrated/General Science) and 3 elective subjects. (Physics, Elective Mathematics + Chemistry OR any other elective relevant to the chosen Program)
Minimum of 5 credit passes in the IGCSE/O-Levels (Mathematics and English mandatory) and 3 passes in the A-Levels. (Elective/Add/Further Mathematics and Physics mandatory).
Minimum of 5 credit passes in the IGCSE/O-Levels (Mathematics and English mandatory) and a minimum score of 4 points in 3 Higher Level (HL) subjects. (Elective/Add/Further Mathematics and Physics mandatory)
Minimum of 50% overall average pass. (subject to approval NAB) Mathematics, English and Physics mandatory
Minimum GPA of 3.0 (Mathematics, English and Physics mandatory)
Electives
AI & Emerging Technologies
- Reinforcement Learning Applications
- Generative AI (GANs, LLMs, Diffusion Models)
- Human-Computer Interaction
- Explainable AI (XAI)
Business & Finance Applications
- Entrepreneurship and Innovation with AI
- Financial Data Analytics (FinTech, Blockchain & AI)
- Customer Behaviour Analytics & Recommendation Systems
- Business Intelligence
Healthcare & Bioinformatics
- Deep Learning for Radiology
- AI Applications in Medicine
- Bioinformatics
- Digital Health & Wearables
Engineering & Robotics
- Robotics and Autonomous Agents
- Intelligent Control Systems
- Computer Graphics & Virtual Reality
- AI for Embedded Systems
Course Outline
- Communication Skills I
- French Language I
- Introduction to Programming
- Technology and Society
- Pre-Calculus
- Introduction to Data Science
- Introduction to Artificial Intelligence
- Introduction to Computing & Programming
- Principles
- Communication Skills II
- French Language II
- Introduction to Philosophy
- Calculus I
- Probability & Statistics I
- Linear Algebra
- Introduction to Economics
- Fundamentals of Innovation and Entrepreneurship (FIE) (Seminar I)
- Calculus II
- Concept of African Leadership I
- Machine Learning Fundamentals
- Probability & Statistics II
- Data Analytics and Visualisation
- Programming for Data Science
- Concept of African Leadership II
- Fundamentals of Innovation and Entrepreneurship (FIE) (Seminar II)
- Applied Regression and Multivariate Analysis
- Computer Vision and Image Processing
- Data Engineering and Database Systems
- Natural Language Processing (NLP)
- Discrete Mathematics
- Fundamentals of Innovation and Entrepreneurship (FIE) I
- Calculus II
- African Leadership I
- Machine Learning Fundamentals
- Probability & Statistics II
- Data Analytics & Visualisation
- Programming for Data Science
- African Leadership II
- Fundamentals of Innovation and Entrepreneurship (FIE) II
- Applied Regression & Multivariate Analysis
- Computer Vision & Image Processing
- Data Engineering & Database Systems
- Natural Language Processing
- Discrete Mathematics
- Cloud Computing
- Professional Ethics & Values
- Reinforcement Learning
- Elective I
- Elective II
- Project Phase I
- Autonomous Agents
- Computer Modelling & Simulation
- Elective III
- Elective IV
- Project Phase II
Why ACity
- Home to students from over 23 countries across africa
- Houses a digital makerspace and a technology & Entrepreneurial center for creative freedom & innovation
- Experienced Faculty with industry experience. Student-to-faculty ratio 5:1
- 70% practical lessons
- Every ACitizen has the opportunity to do a work placement every vacation
