Data Science

Become an expert practitioner of data visualisation, Python programming, and machine learning in this hands-on qualification in data science.

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Programme overview

Gain an overview of data science and machine learning - the skills required to be a data scientist. In the data science fundamentals phase you'll learn how to clean, analyse and visualise data as well as how to effectively communicate the findings.

During the machine learning phase, you'll solve real-world problems by building regression, classification, and unsupervised learning algorithms in Python. This involves data exploration, insight building, and improving and communicating models from a raw and unstructured dataset.
*Course duration for Accelerator and Scholarship tuition options is 12 months, as the coursework is followed by an internship.

Is this course for you?

You’re a newcomer to data science and you want to close the gaps in your analytical skills and knowledge. This course will be beneficial if you’re a professional needing to rapidly upskill and enhance your data science toolkit with theory and practical skills.

Or, you’re a professional working in any of a range of business areas, including but not limited to marketing, sales, finance, and operations. You want to learn how to use data and programming to increase efficiencies and identify new opportunities in your organisation.

Or, you’re new to the world of work and are intrigued by the technical nature of this course and the range of possibilities for a career in tech. How exciting!

Data Science Fundamentals

  • Module 1: Explore101

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

  • Module 2: Data visualisation

    Build dashboards and tell stories with your data to be more persuasive with your findings.

  • Module 3: Python

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

  • Module 4: SQL

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

Machine Learning

  • Module 5: Regression

    Prepare data for modelling, build regression prediction models with Python, and fine-tune them for better results.

  • Module 6: Natural language processing and classification

    Expand your machine learning repertoire into classification, train and predict with models, and learn about NLP.

  • Module 7: Unsupervised learning

    Learn how to cluster unstructured data, build recommender systems and get hands-on with dimensionality reduction.

EXPLORE values Curiosity: Did you know?

11% of people are left handed

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 services

    The career services module (optional for part-time students) contains a wealth of information for conducting an effective job search, CV review, mock interviews, and strategies for building a job opportunity pipeline.

Your success team

ExploreAI Academy's courses include facilitation during working hours. These are world-class scientists, typically with postgraduate degrees or higher, who are available for consultation throughout the course.

  • Zintle Faltein-Maqubela

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

  • Jamie Snyders

    Jamie, a leading facilitator at ExploreAI Academy, 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


    Pay your fees in full before the course starts and enjoy a cost saving. No deposit.
    Applications close 08 January 2024

  • Pay as you Learn

    Pay monthly for the duration of the course. Fees are payable in advance each month.
    Applications close 08 January 2024

  • Scholarship

    Exceptional candidates may qualify for a company-sponsored scholarship. Available to unemployed South African citizens between ages 18-34 only. Assessments and video interview apply.
    Applications close 03 November
    Full-time programme only

  • Accelerator income share agreement

    No upfront cost. Do the course, we help you find a job, and you pay us up to 15% of your monthly salary until you've paid back your tuition. Assessments and video interview apply.
    Applications close 03 November
    Full-time programme only

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