Course layout content

Course overview

The Occupational Certificate: Data Science Practitioner equips learners with the skills to collect, transform, analyse, and present data to solve business problems. Data Science Practitioners bridge the gap between raw data and decision-making by preparing robust datasets, applying statistical and analytical techniques, and producing insightful visual reports. This qualification responds to the increasing demand for skilled data professionals in the era of the Fourth Industrial Revolution (4IR), where organisations rely on big data and analytics to enhance operations and drive innovation.

Learning Outcomes

On completion of this programme, learners will be able to:

Collect large amounts of structured and unstructured data from diverse sources and prepare them for analysis.

Apply analytical and statistical techniques to uncover trends, patterns, and insights within datasets.

Present descriptive analytic reports, visualisations, and data-driven stories that inform business decisions.

Operate ethically and professionally in data-driven environments.

A Qualified Learner Will Be Able To:

Retrieve, clean, and transform data into usable formats.

Apply logical reasoning, programming, and statistical methods to analyse data.

Create visual dashboards, graphs, and reports to communicate findings effectively.

Collaborate ethically in workplace projects, applying design thinking and innovation principles.

Integrate knowledge and practical skills in a capstone project aligned with real-world data problems.

Entry Requirements

Minimum Requirement: A National Senior Certificate or equivalent at NQF Level 4 with Mathematics.
Recognition of Prior Learning (RPL) may provide access for learners with relevant experience or competencies.

International Comparability

This qualification compares favourably with leading global programmes:

Canada: Similar in scope and duration to the Toronto School of Management’s Diploma in Data Analytics Co-op, including knowledge, practical components, and a capstone project.
India: Comparable to AnalytixLabs’ “Data Science with Python” course, covering similar competencies in data analysis, statistics, and visualisation. Unlike some international courses that are vendor-specific (e.g., AWS, IBM), this qualification is vendor-agnostic and includes work experience and ethics modules, providing a broader professional foundation.

Occupational Trainer – NQF Level 5 Certification

This programme is registered as an Occupational Certificate (Data Science Practitioner), NQF Level 5 under the Occupational Qualifications Sub-Framework (OQSF). Successful completion prepares learners for external integrated summative assessment through the QCTO.

Potential Career Opportunities

Graduates of this programme may pursue entry-level and junior roles in data science and analytics, including:

Data Science Practitioner

Data Analyst Assistant / Junior Data Analyst

Data Miner or Data Modeller

Data Custodian

Management Information Analyst

Learning Options

Learning may be offered through:

Classroom-based or blended training with formative assessments.
Workplace learning and mentorship for practical application.
Capstone project integrating knowledge, practical skills, and work experience
External integrated summative assessment conducted by a QCTO-approved Assessment Quality Partner.

Course Details:

NQF Level: 5

SAQA ID: 118708

Accreditation: QCTO

Credits: 185

Duration: 18 Months

Download Course Outline

QCTO Learnerships Data Science Practitioner Level 5

Potential Career Opportunities:

Data Analyst

Database Administrator

Statistical Analyst

Data Governance Analyst

Quality Assurance Analyst

Research Analyst

Junior Data Scientist