Data Science Practitioner

DATA SCIENCE PRACTITIONER

  • NQF: 5
  • SAQA ID. 118708
  • CREDITS:  185

What is a Data Science Practitioner? 

A Data Science Practitioner is tasked with finding answers to crucial business objectives such as optimising business operations, reducing costs, improving customer experience by using Mathematics, Statistics, Computer Science, Information Science and Business domain knowledge. 

Did you know? 

Data science-related job roles are one of the most in-demand tech jobs in the world right now and estimated to be the third-highest paying. According to industry estimates, data scientist jobs roles are growing at 14% and is estimated to create 11 million jobs by 2026.

COURSE OVERVIEW

This qualification builds an understanding of programming such as creating a set of instructions to a computer on how to perform a task using coding and programming languages. Data scientists apply machine learning algorithms to numbers, text, images, video, audio, and other data types to create artificial intelligence (AI) systems that can perform tasks that would normally require human intelligence. This qualification enables students to possess a variety of skill sets that can leverage data and information, that further helps companies to make better strategic decisions.

.

Career Fields

Data Analyst
Data Engineers
Database Administrator
Machine Learning Engineer
Data Scientist
Data Architect
Statistican
Business Analyst
PROGRAMME TITLE
NQF
SAQA ID
CREDITS
DATA SCIENCE PRACTITIONER
5
118708
185
Admission Requirements
  • NQF Level 4 with Mathematics

Certification and Examination 

On successful completion of the programme, the student will receive a statement of result from Berea College of Technology and upon meeting the EISA requirements, receive an Occupational Certificate: Data Science Practitioner from the QCTO. 

EISA is a single, national assessment which leads to competent learners being awarded Occupational Certificates. It is an integral and critical component of QCTO’s quality assurance system, as it ensures that the assessment of occupational qualifications, part-qualifications and trades is standardised, consistent and credible. Qualifying for External Assessment: To qualify for an external assessment, learners must provide proof of completion of all required knowledge and practical modules by means of statements of results and a record of completed work experience

Duration and Work-Integrated Learning

2 YEARS FULL TIME

Study Materials
  • Prescribed textbook lists will be provided by the academic department at your campus. Students will receive electronic versions of the study guides for this programme. Study material is also available online on the learner management system, Moodle. 

Pricing

Enquire at the Berea College of Technology campus for a current programme pricelist. 

Additional Costs

Students must make provision for additional items such as textbooks, stationery, supplementary examinations, research costs and printing of study guides etc.

For more information on this course and for further study options, visit www.bct.ac.za 

WHAT IS THIS COURSE ?

Knowledge Modules

Introduction to Data Science and Data Analysis, 

Logical Thinking and Basic Calculations: Refresher 

Computers and Computing Systems 

Computing Theory 

Basic Statistics for Data Analytics 

Statistics Essentials for Data Analytics 

Data Science and Data Analysis 

Data Analysis and Visualisation 

Introduction to Governance, Legislation and Ethics 

Fundamentals of Design Thinking and Innovation 

4IR and Future Skills

Practical Modules

Apply Logical Thinking and Math’s Refresher 

Apply Code to Use a Software Toolkit/Platform in the Field of Study or Employment 

Use Spreadsheets to Analyse and Visualise Data 

Use a Visual Analytics Platform to Analyse and Visualise Data 

Apply Statistical Tools and Techniques 

Collect and Pre-Process Large Amounts of Unruly Data 

Apply Data Analysis Techniques to Uncover Patterns and Trends in Datasets 

Prepare and Present Descriptive Analytic Reports for Decision Making 

Participate in a Design Thinking for Innovation Workshop 

Collaborate Ethically and Effectively in the Workplace

Work Experience Modules

Data Collection and Pre-processing Processes 

Statistical Data Analysis Processes 

Data Visualisation and Reporting Processes 

Capstone Project Using an Appropriate Toolkit 

DATA SCIENCE PRACTITIONER