Python for Data Science
Master Python from scratch and apply it to real data analysis problems.
About this course
Learn Python programming with a data-first approach. You will go from writing your first line of Python to analysing real datasets with pandas and NumPy, creating visualisations with Matplotlib, and building your first predictive model. This course is the recommended starting point for any aspiring data scientist or ML engineer.
Target audience: Aspiring data scientists, analysts switching to Python, business professionals
What you will learn
- Python programming
- pandas
- NumPy
- Data visualisation
- Exploratory data analysis
Course syllabus
9 modules · video + projects
- 1Python basics: variables, types, control flow, and functions
- 2Working with lists, dictionaries, and comprehensions
- 3Reading and writing files; working with CSV and JSON
- 4NumPy: arrays, vectorised operations, and broadcasting
- 5pandas: DataFrames, indexing, groupby, and merging
- 6Data cleaning: missing values, outliers, and type conversions
- 7Visualisation with Matplotlib and Seaborn
- 8Introduction to scikit-learn: your first model
- 9A complete data analysis project end to end
Prerequisites
- –Basic computer literacy
Frequently asked questions
Which Python version does this course use?
Python 3.12 — the current stable release. All code examples and notebooks work on Windows, macOS, and Linux.
Do I need to install anything?
No local setup is required. All exercises run in browser-based notebooks. Optional setup instructions for a local Anaconda environment are provided for learners who prefer that.
How does this differ from a general Python course?
Every example and exercise uses real data. You will spend minimal time on abstract programming concepts and most of your time manipulating, analysing, and visualising datasets.
Ready to start Python for Data Science?
Join 8,700+ learners already enrolled. Self-paced, certificate on completion.