Occupational Certificate: Data Science Practitioner

This programme is designed to equip learners with theoretical knowledge, practical skills, and workplace experience in data science and analytics. In the context of the Fourth Industrial Revolution (4IR), data analysis has become essential for modern business environments. This qualification supports learners in developing competencies aligned with innovation, critical thinking, and ethical data practices.

Target Audience

• Aspiring data analysts and data scientists
• Professionals transitioning into data-related roles
• Individuals seeking an NQF-accredited qualification in data analytics
• Matriculants and entry-level learners with an interest in computing and analytics

By the End of the Programme, Learners Will Be Able To:

• Understand and apply core data science and analytics principles
• Use industry-relevant tools for data analysis and visualisation
• Apply ethical, legal, and governance considerations in working with data
• Communicate insights effectively to support decision-making
• Develop 4IR-aligned competencies in innovation and critical thinking

Qualifying learners working in data science will have the necessary knowledge, skills, and attitudes to function more effectively in a professional manner, add value to their job, and enhance their ability to follow and implement policies and procedures. It is against this background that the programme has been clustered into six modules.

Module 1: Introduction to Data Science and Analysis

PURPOSE OF THE PROGRAMME

• 251102 – 001 – 00 – KM - 01: Introduction to Data Science and Data Analysis – 6 credits
• 251102 – 001 – 00 – KM - 02: Logical Thinking and Basic Calculations – 4 credits
• 251102 – 001 – 00 – PM - 01: Apply Logical Thinking and Maths Refresher – 3 credits

Total Credits: 13
Total Number of Days: 5

Module 2: Understanding Computing Theory

• 251102 – 001 – 00 – KM - 03: Computers and Computing Systems – 4 credits
• 251102 – 001 – 00 – KM - 04: Computing Theory – 2 credits
• 251102 – 001 – 00 – PM - 02: Apply Code to use a Software Toolkit/Platform in the Field of Study or Employment – 4 credits

Total Credits: 10
Total Number of Days: 5

Module 3: Basic Statistics for Data Analytics

• 251102 – 001 – 00 – KM - 05: Basic Statistics for Data Analytics – 10 credits
• 251102 – 001 – 00 – KM - 06: Statistics Essential for Data Analytics – 4 credits
• 251102 – 001 – 00 – PM - 05: Apply Statistical Tools and Techniques – 4 credits

Total Credits: 18
Total Number of Days: 5

Module 4: Data Science and Data Analysis

• 251102 – 001 – 00 – KM - 07: Data Science and Data Analysis – 12 credits
• 251102 – 001 – 00 – PM - 06: Collect and Pre-process Large Amounts of Structured and Unstructured Data – 12 credits
• 251102 – 001 – 00 – PM - 07: Apply Data Analysis Techniques to Uncover Patterns and Trends in Datasets – 12 credits
• 251102 – 001 – 00 – PM - 08: Prepare and Present Descriptive Analytic Reports for Decision Making – 12 credits

Total Credits: 48
Total Number of Days: 5

Module 5: Data Science and Visualisation

• 251102 – 001 – 00 – KM - 08: Data Science and Visualisation – 16 credits
• 251102 – 001 – 00 – PM - 03: Use Spreadsheets to Analyse and Visualise Data – 3 credits
• 251102 – 001 – 00 – PM - 04: Use a Visual Analytics Platform to Analyse and Visualise Data – 4 credits

Total Credits: 23
Total Number of Days: 5

Module 6: Becoming a Professional Data Analyst

Total Days: 31 (Includes a day for the FISA completion)

The learners will be expected to engage in the following workplace activities:

• 251102 – 001 – 00 – KM - 09: Introduction to Governance, Legislation and Ethics – 3 credits
• 251102 – 001 – 00 – KM - 10: Fundamentals of Design Thinking and Innovation – 4 credits
• 251102 – 001 – 00 – KM - 11: 4IR and Future Skills – 1 credit
• 251102 – 001 – 00 – PM - 09: Participate in a Design Thinking for Innovation Workshop – 3 credits
• 251102 – 001 – 00 – PM - 10: Collaborate Ethically and Effectively in the Workplace – 3 credits

Total Credits: 14
Total Number of Days: 5

Workplace Experience Specifications

• 1251102 – 001 – 00 – WM - 01: Data Collection and Pre-processing Processes – 16 credits
• 1251102 – 001 – 00 – WM - 02: Statistical Data Analysis Processes – 16 credits
• 1251102 – 001 – 00 – WM - 03: Data Visualisation and Reporting Processes – 16 credits
• 1251102 – 001 – 00 – WM - 04: Capstone Project using an Appropriate Toolkit – 12 credits

Total Credits: 60