Using to learn Python

Powering success in
Data Science careers is focussed on learning and development, providing real-world simulated projects with instant feedback on code quality and personalised recommendations on learning. For learners who opt in, we provide opportunities to showcase your technical portfolio and connect with employers.

Example projects

Security lock
Classification of risk profiles for the insurance industry

Use Python, Pandas, Scikit-learn to create a machine learning algorithm that can classify risk profiles for the insurance industry.

Stack of servers
Data Analysis of all Hackernews posts

Learn how to analyse huge amounts of raw data using Python and Spark. Get information from Hackernews posts.

Stack of books
Classification of topics for newsgroup articles

Learn how to process natural language and classify newsgroup article topics with Python, Scikit-learn and Spacy.

Photo camera
Classification of images of clothes for an online retailer

Create a deep learning algorithm using Python, Keras and Tensorflow to identify and classify images of clothes.

How works for students


Choose a project

Begin a case study or real-world project on


Write code

Write code where you feel comfortable and submit via either git or Web IDE


Submit code

Submit your code to KATE, the learning engine behind


Receive feedback

Receive instant personalised feedback: code quality, code performance, correctness and further reading materials


Iterate and improve

Learn by doing and build a portfolio of real-world projects


Connect with employers

Connect with employers on the platform by making your portfolio available or through organised events