Introduction to Data Analysis and Machine Learning in Python (In-Person)

Learn practical tasks to analyse data effectively.

Session Information

This session focuses on the practical tasks required to analyse data effectively. You will learn how to use the pandas package to clean and combine data, as well as seaborn to create visual charts. The course also introduces the framework for Machine Learning with scikit-learn, showing you how to build simple models that make data-driven decisions.

Audience Level:

You should have completed "Introduction to Python" (also part of Bristol Data Week) or have a basic understanding of Python programming.

Advance requirements/set up:

You will need a laptop and a Google account to use Colab https://colab.google/

Intended Learning Outcomes

• Know how to read data files and resolve common formatting issues.
• Create plots and charts to visualize and explore your data.
• Understand how to fit a machine learning model to your data.
• Learn how to split data into "training" and "testing" sets to evaluate your model's performance.

Code of Conduct

Please look at our Code of Conduct for all online and in-person events organised by the JGI.

Bristol Data Week 2026

This event is part of Bristol Data Week 2026, organised by the Jean Golding Institute taking please from Monday 1 June – Friday 5 June 2026. Bristol Data Week is a university-wide umbrella event bringing together academia, industry, community organisations, policy makers and the public to explore the power of data science and AI in addressing real-world challenges.