Data Science Practitioner
Full Qualification
FQ
Information Technology and Computer Sciences
The purpose of this qualification is to prepare learners to operate in data-driven environments. It equips aspiring Data Practitioners with the ability to collect, manage, analyse and present data to support business decisions. The qualification lays a strong foundation for entry-level roles in data or continued studies in data science
Learnership Duration: 12 - 18 Months
SAQA ID : 118708
NQF Level 5 - 185 Credits (1850 Notional Hours)
Notional Hours split into:
Self-paced online e-learning, Virtual Classrooms, In-real-life practical days, Implementing Knowledge in the Workplace, Time Spent on Portfolio of Evidence (PoE), Assessment and Feedback Sessions
Data Science Practitioner Qualification Outcomes
The learners completing the qualification will be able to:
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Collect large volumes of structured and unstructured data from primary and secondary sources, and transform it into usable formats.
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Apply data analysis techniques, including statistical methods and queries, to uncover trends and patterns that address business-related problems.
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Prepare and present descriptive analytical reports using programming, visualisation tools, and storytelling techniques to communicate insights effectively
"If learners already hold a BSc in Computer Science, Statistics, Applied Mathematics, or Data Science—or a related STEM degree—they may qualify for Recognition of Prior Learning (RPL) against certain Knowledge Modules in this qualification."
Data Science Practitioner- % Time Spent Breakdown
The time spent learning is split into Online Self-Paced Learning (by themselves), virtual classrooms and in-real-life sessions (With Us, Diverse Conversations). The time spent on workplace tasks is the time spent with the approved workplace company (With You), which will give the learners the necessary experience to successfully complete this qualification.
As we have not implemented the Data Science Practitioner Qualification just yet, we cannot give an accurate estimation of the % Time Spend Table at this time
Data Science Practitioner- Qualification Curriculum Content
The Qualification has been structured around the Curriculum Document as a standard from Services Seta and QCTO. For you, as a business entity, to claim your B-BBEE skills development points, learners are required to complete Knowledge Modules (KM's), Practical Modules (PM's) and Workplace Modules (WM's).
Knowledge Modules (KM's)
serve as the foundational learning components that provide learners with the theoretical understanding required for effective performance in the role.
Implemented Month 1
NQF 4 (66 credits)
Total Notional Hours = 660 hrs
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KM01: Introduction to Data Science and Data Analysis
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KM02: Logical Thinking and Basic Calculations: Refresher
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KM03: Computers and Computing Systems
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KM04: Computing Theory,
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KM05: Basic Statistics for Data Analytics
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KM06: Statistics Essentials for Data Analytics
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KM07: Data Science and Data Analysis
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KM08: Data Analysis and Visualisation
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KM09: Introduction to Governance, Legislation and Ethics
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KM10: Fundamentals of Design Thinking and Innovation
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KM11: 4IR and Future Skills
Practical Modules (PM's)
are designed to develop the hands-on skills needed to apply theoretical knowledge in real-world scenarios, bridging the gap between classroom learning and workplace performance.
NQF 5 (59 credits)
Total Notional Hours = 590 hrs
Implemented Month 2 - 4
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PM01: Apply Logical Thinking and Maths Refresher
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PM02: Apply Code to use a Software Toolkit/Platform in the Field of Study or Employment
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PM03: Use Spreadsheets to Analyse and Visualise Data
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PM04: Use a Visual Analytics Platform to Analyse and Visualise Data Conflicts
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PM05: Apply Statistical Tools and Techniques
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PM06: Collect and Pre-Process Large Amounts of Structured and Unstructured Data
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PM07: Apply Data Analysis Techniques to Uncover Patterns and Trends in Datasets
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PM08: Prepare and Present Descriptive Analytic Reports for Decision Making
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PM09: Participate in a Design Thinking for Innovation Workshop
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PM10: Collaborate Ethically and Effectively in the Workplace
Workplace Modules (WM's)
focus on the real-time application of knowledge and skills in an actual work environment, ensuring that learners are work-ready and capable of operating professionally and ethically within the industry.
Implemented Month 1 - 12
NQF 5 (60 credits)
Total Notional Hours = 600 hrs
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WM01: Data Collection and Pre-processing Processes
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WM02: Statistical Data Analysis Processes
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WM03: Data Visualisation and Reporting Processes
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WM04: Capstone Project using an Appropriate Toolkit
Whilst implementing this curriculum, learners can assist in collecting and analysing data while learning how to turn information into insights that support smarter business decisions.
