Go a Step Further with Smart Tech

Artificial intelligence (AI) makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. Most AI examples that we hear about today – from chess-playing computers to self-driving cars – rely heavily on deep learning and natural language processing.

Using these technologies, computers can be trained to accomplish specific tasks by processing large amounts of data and recognizing patterns in the data in Health Care, Agriculture, Transportation, Engineering, Manufacturing, Retail, Banking, etc.

These advanced in AI and Machine Learning offer tremendous opportunities across the spectra of human endeavors and are poised to reshape future technologies and workforces.

2021 intake is open

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Want to know more? Enter your information below to learn more about the ACity Artificial Intelligence Programme.


Top Careers in Artificial Intelligence

Sudhakar Shinde

Graduating students of this programme will be able to select, create, apply, integrate, and administer computing technologies in order to meet the needs of users within societal and organizational contexts. Some top career options include;

 Business Intelligence Developer  Machine Learning Engineer
 Computer Vision Engineer  Applications Developer
 Cyber Security Analyst  AI Research Scientist
 Application Analyst

Entry Requirements

Minimum C6 in 6 subjects including 3 core subjects (Maths and English mandatory) and 3 elective subjects. (Elective/Add/Further Maths and Physics mandatory)

Minimum D or a pass in 6 subjects including 3 core subjects (Maths and English mandatory) and 3 elective subjects. (Elective/Add/Further Maths and Physics mandatory).

Minimum of 5 credit passes in the IGCSE/O-Levels (Maths and English mandatory) and 3 passes in the A-Levels. (Elective/Add/Further Maths and Physics mandatory).

Minimum of 5 credit passes in the IGCSE/O-Levels (Maths and English mandatory) and a minimum score of 4 points in 3 Higher Level (HL) subjects. (Elective/Add/Further Maths and Physics mandatory)

Minimum of 50% overall average pass. (subject to approval NAB) Maths, English and Physics mandatory

Minimum GPA of 3.0 (Maths, English and Physics mandatory)

What To Know
More Information


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Course Outline

 Communication Skills

 French Language

 Fundamentals of Innovation and Entrepreneurship (FIE) Seminar I

 Introduction to Programming with Python

 Physical Sciences

 Technology and Society

 Pre-Calculus (with MATLAB)

 Data Analysis using MS Excel

 Fundamentals of Innovation and Entrepreneurship (FIE) Seminar II

 Logic and Critical Thinking

 Text and Meaning

 Analytic Geometry and Calculus I (with MATLAB)

 Principles of Microeconomics

 Programming in C

 Financial Accounting I

 Introduction to Artificial Intelligence and Robotics

 Fundamentals of Innovation and Entrepreneurship (FIE) I

 Leadership Seminar I

 Analytic Geometry and Calculus I (with MATLAB)

 Fundamentals of Logic Design

 AI: Representation and Problem-Solving

 Data Structures and Algorithms

 Introduction to Computer Systems

 Object Oriented Programming with C++

 African Studies

 Fundamentals of Innovation and Entrepreneurship (FIE) II

 Probability, Statistics and Reliability (with MATLAB)

 Applied Linear Algebra (with MATLAB)

 Computer Architecture and Organisation

 Design and Analysis of Algorithms

 Signals and Systems

 Leadership Seminar II

 Applied Probability and Computing (with MATLAB)

 Discrete Mathematics (with MATLAB)

 Digital Signal Processing

 Great Theoretical Ideas in Computer Science

 Machine Learning

 Object Oriented System Design

 Project Management, Engineering Economics and Risk Analysis

 Computational Neural Networks

 Computer Vision

 Industry Internship

 Natural Language Processing

 Research Methods in Computing

 Autonomous Agents

 Computational Perception

 Intermediate Data Analytics

 Introduction to Deep Learning

 Project Phase I

 Speech Processing

 Professional Ethics and Values

 Advanced Data Analytics

 Intermediate Deep Learning

 Design of Artificial Intelligence Products

 Project Phase II

2021 intake is open

Our Unique Learning Pillars


  • Experiential Learning

    Hands-on learning to prepare students to readily apply concepts, to easily integrate into the workspace.


  • Contextual Learning

    Solving real grass-root problems to expose students to the local context and develop empathy towards the continent’s progress.


  • Unified Learning

    A project-based approach that combines concepts across courses to connect the dots and enable unified learning.


  • Extensional Learning

    Arms students with a viable toolkit to help them confront real-life issues, they may not have encountered during their academic life, squarely.