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Artificial Intelligence Software Developer

SQAQ ID: 118792, NQF Level 5, Credits 209 | 18–24 Months | Blended (Online + In‑Person Practical)

  • NQF Level: NQF Level 5
  • Duration: 18 - 24 Months
  • Credits: 209
  • Mode: Online

Purpose

The Occupational Certificate: Artificial Intelligence Software Developer is a future-focused, work-integrated qualification designed to prepare learners for practical careers in the fast-growing field of artificial intelligence (AI). It serves as a direct response to the increasing demand for professionals who can build, test, deploy, and maintain intelligent systems across real operational environments.

Unlike traditional academic degrees that often emphasise theoretical knowledge, this qualification is intentionally skills-based and outcome-driven. Learners are equipped with applied coding skills, analytical thinking capabilities, and hands-on experience in machine learning, deep learning, and data-driven development. These competencies are applicable across sectors such as finance, healthcare, logistics, retail, manufacturing, and emerging technology industries.

Registered with the Quality Council for Trades and Occupations (QCTO) and aligned with South Africa’s Fourth Industrial Revolution (4IR) strategy, the qualification also reflects global digital transformation trends. It provides an accessible and recognised entry point for school leavers, career changers, entrepreneurs, and working professionals seeking to enter or advance within the AI and technology economy.

Entry Requirements

Direct Entry Route

Applicants must hold an NQF Level 4 qualification (Matric or equivalent) with Mathematics or Mathematical Literacy.

Applicants with Mathematical Literacy may be required to complete an additional Mathematics bridging module.

Required Documentation:

Recently certified copy of South African ID or valid Passport

Recently certified copy of NQF Level 4 qualification certificate

Recognition of Prior Learning (RPL) Entry Route

Applicants who do not meet the formal NQF Level 4 requirement may apply through the Recognition of Prior Learning (RPL) entry route. This pathway recognises relevant workplace experience, informal learning, and demonstrated competence.

This route is suitable for:

Individuals without Matric or an NQF Level 4 qualification

Applicants with relevant experience in IT, coding, data handling, or technical environments

Self-taught individuals or entrepreneurs with informal or non-formal training

All RPL-approved applicants will be required to complete an additional Mathematics bridging module.

Additional Documentation for RPL Applicants:

Detailed CV outlining relevant roles and experience

Employer confirmation letter(s), where applicable

Certificates or proof of informal or non-formal training

Optional portfolio of evidence (projects, code samples, digital work)

RPL Application Fee

A non-refundable RPL Application Fee of R1,95 0 is mandatory for all applicants using this access route.

RPL Assessment Process

Your documents will be reviewed by the RPL Admissions Panel.

If necessary, an interview or skills test may be conducted.

Applicants will receive a formal outcome within 30 days.

If successful, you will be required to enrol and complete the Mathematics bridging module before proceeding with the core programme.

Learning Outcomes

On successful completion of this qualification, the learner will be able to:

Analyse real-world problems and translate them into practical AI-based solutions.

Apply mathematical, statistical, and analytical principles to support data-driven decision-making.

Design, develop, and implement machine learning and deep learning models using Python and industry-standard tools.

Collect, prepare, analyse, and visualise data to support intelligent system development.

Build, test, deploy, and maintain AI solutions within ethical, legal, and governance frameworks.

Apply design thinking principles to develop innovative, user-centred AI solutions.

Work effectively within technical teams, applying collaboration, communication, and professional practices.

Operate within workplace environments, demonstrating job readiness, accountability, and applied competence in AI development roles.

Curriculum

Knowledge Modules (KM) – 86 Credits

Module Name

NQF Level

Credits

Overview of AI

4

2

Intro to Mathematics & Statistics

4

10

Analytical Thinking & Problem Solving

4

3

Data, Databases & Visualisation

4

8

Computing Theory

4

8

Intro to AI, Machine Learning & Deep Learning

4

5

Governance, Legislation & Ethics

4

1

Fundamentals of Design Thinking & Innovation

4

1

4IR and Future Skills

4

4

Artificial Intelligence

5

12

Machine Learning

5

16

Deep Learning

5

16

Practical Modules (PM) – 63 Credits

Module Name

NQF Level

Credits

Mathematics & Statistics for Programming

4

8

Analytical Thinking & Decision-Making

4

2

Analyse & Visualise Data (Spreadsheets)

4

4

SQL for Databases

5

4

Build AI with Python

5

8

Python Data Scraping & SQL

5

4

Machine Learning AI in Python

5

6

Deep Learning AI in Python

5

10

Deep Learning AI in TensorFlow

5

10

Ethics & Team Collaboration

4

3

Design Thinking Workshop

4

4

Workplace Modules (WM) – 60 Credits

Module Name

NQF Level

Credits

AI Solution Design Interpretation & Development

5

20

AI Solution Performance Testing

5

20

AI Solution Deployment & Maintenance

5

20

What Makes This Qualification More Valuable Than a Traditional Academic Degree?

This qualification is modular, industry-aligned, and agile, allowing individuals to enter the workforce faster, continue learning on the job, and pivot into various AI-related fields without being locked into rigid academic pathways.

Occupational Certificate

Traditional Academic Degree

Practical, real-world coding & deployment

Mostly theoretical understanding

Workplace modules & experience built-in

Internship optional or separate

Skills-focused: Python, AI, ML, Deep Learning

Often general IT theory or mathematics-heavy

Shorter, faster route to employment

3–4 years to complete

Open access (NQF 4 minimum)

University admission requirements

Aligned with employer needs & 4IR workforce planning

Often not aligned with market gaps

Customisable pathways for upskilling, RPL, and blended delivery

Limited flexibility for part-time or modular study

Career Opportunities

Graduates of this qualification may pursue employment or progression in roles such as:

Artificial Intelligence Developer

Machine Learning Engineer

Business Intelligence (BI) Developer

AI Technician

Junior AI Researcher

Data and Analytics Support Roles

The qualification also provides a foundation for further occupational specialisation, professional development, and career progression within the broader ICT and data science ecosystem.

Pricing

2026 Fee Structure

Fee Type

Amount (ZAR)

Description

First-Time Application Fee

R 250

Non-refundable, paid at time of application submission

Once-Off Enrolment Fee

R 2,500

Non-refundable, Payable upon admission to secure your placement

Full Course Fee (Semester Plan)

R 50,000

Payable in 4 equal semester instalments of R12,500 each

Full Course Fee (Per Month Instalment Plan)

R 63,150

Payable as R2,150 per month x 30 Months

Other Fees

Additional Services

Amount (ZAR)

Description

RPL Application Fee

R 1,950

For Recognition of Prior Learning (RPL) route

Final External Exam Fee

R 3,500

Payable before scheduling the External Integrated Summative Assessment (EISA)

Frequently Asked Questions

What makes this a “real AI developer” programme, not just AI theory?

It trains you to build AI functionality into software applications by integrating AI logic and algorithms into real IT deliverables.

What level is this, and what does that mean for career value?

It’s an Occupational Certificate (NQF Level 5, 209 credits), a substantial, job-focused pathway rather than a short skills workshop.

Will these skills translate internationally?

Yes, because the focus is on AI-in-software development work (building, integrating, and maintaining AI features) which is the same work pattern used in global tech teams.

Why choose “AI Software Developer” instead of “Data Science”?

This route is for people who want to develop, ship AI features inside apps and systems, not only analyse data, but turn AI into working software products.

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