Python for AI and Machine Learning

About this course

No coding experience? Start here.

Artificial intelligence looks impenetrable from the outside: a wall of maths, jargon and frameworks. This course takes you from your very first line of Python to training your own deep learning models, one step at a time, with nothing assumed.

You will begin with Python fundamentals - variables, loops, functions, data structures - then learn to clean, analyse and visualise real data with Pandas, NumPy and Matplotlib. From there you move into machine learning with Scikit-Learn, and on to deep learning with TensorFlow and PyTorch. Everything runs in Google Colab, so you get free GPU access and never have to fight an installation.

The four projects you will buildA crop health predictor that classifies plant condition from field data

An image classifier built with a neural network

An air quality forecaster using time-based dataA custom machine learning application of your own design

Why these projects matter

They are drawn from agriculture, healthcare and environmental science rather than toy datasets, so the work you finish with is something you can show an employer or adapt to your own research.

What you get

Step-by-step lessons that assume no prior programming knowledge

Downloadable notebooks and datasets to follow along withA finished portfolio of four projects by the endQ&A support from the instructor throughout

Taught by Dr. Azad Rasul, a geospatial data scientist and Assistant Professor, with over 150,000 students enrolled across his Udemy courses.

Enrol now and write your first AI model this week.

Prices, discounts and availability are set by Udemy. We may earn a commission when you purchase through links on this site.