Knowledge Modules

1. KM-01 Overview of Artificial Intelligence, Level 4, 2 Credits.

2. KM-02 Introduction to Mathematics and Statistics, Level 4, 10 Credits.

3. KM-03 Analytical Thinking and Problem Solving, Level 4, 3 Credits.

4. KM-04 Data, Databases and Data Visualization, Level 4, 8 Credits.

5. KM-05 Computing Theory, Level 4, 8 Credits.

6. KM-06 Introduction to Artificial Intelligence, Machine Learning, Deep Learning, Level 4, 5 Credits.

7. KM-10 Introduction to Governance, Legislation and Ethics, Level 4, 1 Credit.

8. KM-11 Fundamentals of Design Thinking and Innovation, Level 4, 1 Credit.

9. KM-12 4IR and Future Skills, Level 4, 4 Credits.

10. KM-07 Artificial Intelligence, Level 5, 12 Credits.

11. KM-08 Machine Learning, Level 5, 16 Credits.

12. KM-09 Deep Learning, Level 5, 16 Credits.

Practical Skills Modules

1. PM-01 Mathematics and Statistics for Programming, Level 4, 8 Credits.

2. PM-02 Problem Definition, Analytical Thinking and Decision-Making, Level 4, 2 Credits.

3. PM-03 Access, Analyze and Visualize Structured Data Using Spreadsheets, Level 4, 4 Credits.

4. PM-04 Use SQL to Communicate with a Database, Level 5, 4 Credits.

5. PM-05 Build a simple AI solution using Python, Level 5, 8 Credits.

6. PM-06 Use Python Data Scraping to Populate Database Table in SQL, Level 5, 4 Credits.

7. PM-07 Use Machine Learning to Build an AI solution in Python, Level 5, 6 Credits.

8. PM-08 Use Deep Learning to Build an AI Neural Network Architecture in Python, Level 5, 10 Credits.

9. PM-09 Use Deep Learning to Build an AI Neural Network Architecture in TensorFlow, Level 5, 10 Credits.

10. PM-10 Function Ethically and Effectively as a Member of a Multidisciplinary Team, Level 4, 3 Credits.

11. PM-11 Participate in a Design Thinking for Innovation Workshop, Level 4, 4 Credits.

Work Experience Modules:

1. WM-01 AI Solution Design Interpretation and Development, Level 5, 20 Credits.

2. WM-02 AI Solution Performance Testing, Level 5, 20 Credits.

3. WM-03 AI Solution Deployment, Modification and Improvement, Level 5, 20 Credits.

The minimum entry requirement for this qualification is:

– NQF Level 4 qualification.

Full Time, Contact (Hybrid) Learning

– Duration 18 Months

– Theory modules classes can be attended on campus AND/OR Online

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Full Time, Online Learning

– Duration 18 Months

– Classes conducted over 10 sessions/week (± 3.5 days/week)

– Online (Hybrid) Learning through Microsoft Teams

Entry-Level Roles

– AI Developer Intern/Junior AI Developer

– Data Analyst/Junior Data Scientist

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Mid-Level Roles

– AI Software Developer/Engineer

–  Machine Learning Engineer

– Data Engineer

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Senior-Level Roles

– Senior AI Engineer/Developer

– AI Architect

– Data Scientist (Advanced Role)

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Leadership and Executive Roles

– AI Product Manager

– AI Research Scientist

– AI Consultant

– Chief AI Officer/Head of AI

On successful completion of this program, you may be able to articulate into the following:

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Horizontal Articulation:

– Occupational Certificate: Computer Technician; NQF Level 5.

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Vertical Articulation:

– Diploma in Information Technology; NQF Level 6.