Become an expert practitioner of Python programming, SQL and database technology, and the ins and outs of big data in this hands-on qualification in data engineering.

  • Course Duration:
    12 months

    At 15 hrs/week

  • Course starts:

    January 16, 2023

    Applications Close:

    January 15, 2023

    Basic Analytical Background

Program overview

Gain an overview of data-related fundamentals and advanced big data techniques. These are the skills required to be a data engineer. In the Fundamentals phase you'll learn how to identify and state problems clearly, how to code effectively in SQL and Python, and get to grips with AWS and a variety of the AWS tools we'll use to work with data in the cloud.

During Big Data, you'll do a deep dive into all the technicalities and tools used to handle big data. You'll be able to analyse and identify the storage and processing requirements for data you might be dealing with. You'll gain the knowledge to build end-to-end pipelines to move data around. And you'll have an understanding of how to deal with large datasets in a distributed manner.

Full-time: 6 months at 40+ hours per week
Part-time: 12 months at 15+ hours per week

Is this course for you?

This course is for someone who really wants to lean in to the burgeoning world of big data. You should have a passion for hacking things together, which is what you do in data engineering when integrating the variety of tools on offer. You should enjoy working in complex environments on complex problems. And you should be comfortable context switching between multiple tools to arrive at a desired result.

Data engineering is useful to technical workers in all industries: from marketing to sales, finance to operations, engineering to executive leadership. This course is technical in nature. It is recommended that you have an analytical background (having worked with mathematics or statistics). Experience in at least one programming language would be beneficial but not required.


  • Sprint 1: EXPLORE 101

    Understand common data terminology and learn how to define your problems before you tackle them.

  • Sprint 2: SQL for Data Science

    Work with SQL to use databases for storing, reading and updating data.

  • Sprint 3: Python for Data Science

    Learn the fundamentals of Python programming: working in notebooks; logic and functions; and data structures.

  • Sprint 4: Cloud Computing

    Get to grips with everything AWS. Learn about a host of services offered by AWS and work hands-on with them to work with data and applications in the cloud.

Big Data

  • Sprint 5: Storing Big Data

    Connect large data sources in the cloud to create data lakes. Understand data analytics as it pertains to big data and data lakes.

  • Sprint 6: Moving Big Data

    This sprint is all about data pipelines. Learn how to get your data where you want it and when, using tools like Apache Hadoop and Spark.

  • Sprint 7: Processing Big Data

    Gain practical experience writing functions in Apache Spark which test quality metrics. Learn how to document data lineage.

Explore values curiosity: Did you know?

The average person falls asleep in 7 minutes

Value-added services

Alongside the technical content, you'll have access to the following services during your time on the course.

  • A proven job search framework

    We’ve developed a framework for a successful job search. Nearly every single graduate who has followed these guidelines has been hired.

  • Thrive

    Our personal development curriculum, Thrive, contains a host of additional content on job searching, interview preparation, technical portfolio curation, cover letter writing, and more.

  • Career coaching

    You'll have access to a dedicated career coach to guide you through an effective job search, including resume review, mock interviews, and strategies for building a job opportunity pipeline.

Your teaching team

EXPLORE's courses include facilitation by default. Our facilitators are world-class scientists, typically with postgraduate degrees or higher, who are available to contact throughout the duration of the course.

  • Zintle Faltein-Maqubela

    Zintle, head teacher at EDSA, comes from the technical background of biology, and is a proud alumnus of EXPLORE's very own data science course.

  • Jamie Snyders

    Jamie, a leading facilitator at EDSA, holds a BSc in theoretical physics, and went on to do honours in applied mathematics. He's perfectly suited to help deliver our technical course content, giving students the best chance of success.

  • Chris Barnett

    Chris hails from a rich academic background and holds BSc, MSc, and PhD degrees in chemistry. His rigourous research career positions him perfectly to deliver and provide support in our technical data qualifications.

Payment plans

  • Upfront Payment

    Pay your fees in full before the course starts and enjoy a cost-saving. No deposit.
    Applications close: 10 July 2022

  • Pay as you Learn

    Pay monthly for the duration of the course and no further. Fees are payable in advance each month.
    Applications close: 10 July 2022

  • EXPLORE Loan

    Pay your tuition fees over an extended 36-month period, starting from the first month of the course.
    Applications close: 10 July 2022

  • Accelerator

    No upfront cost. Do the course, we help you get a job, and you pay us up to 15% of your gross monthly salary until you've paid back your tuition.
    Qualifying testing and interview apply.
    Applications close: 10 June 2022

Upfront Payment
$350 Per month for duration of course

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We’ve got your interests at heart

At EXPLORE we believe that talented individuals should be able to access opportunities to uncover their potential and realise their dreams. We are dedicated to make learning more accessible.
The EXPLORE loan is designed to do exactly that. With 36 months to pay off your studies, our intention is to offer a competitive and affordable financing option.
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