AI & ML step-by-step tutorials
A free, hands-on series of Google Colab notebooks that take you from the fundamentals of machine learning to applied network-security use cases. Open any notebook in your browser, run it, and experiment. No setup required.
Your first steps in machine learning: the workflow, tools and core ideas.
Open in Colab → Tutorial 2Cleaning, encoding, scaling and preparing data so your models can learn from it.
Open in Colab → Tutorial 3Predicting startup success with multiple linear regression, end to end.
Open in Colab → Tutorial 4Building and visualising a logistic regression classifier and its decision boundary.
Open in Colab → Tutorial 5Training, tuning and interpreting decision-tree classifiers.
Open in Colab → Tutorial 6Your first neural network: layers, activations, training and evaluation.
Open in Colab → Tutorial 7Applying ML to spot anomalies in network-traffic data, a core security use case.
Open in Colab → Tutorial 8Reducing and visualising high-dimensional data with PCA, LDA and t-SNE.
Open in Colab → Tutorial 9Constructing a deeper ANN from scratch and training it on real data.
Open in Colab → Tutorial 10An AI model that distinguishes normal from malicious network traffic.
Open in Colab →Watch & listen
The full lecture series that accompanies these notebooks. Watch the concepts explained step by step, then run the code yourself.
Audio discussions on AI, machine learning and cybersecurity. Ideal for commutes and revision between hands-on sessions.
These tutorials, lectures and materials can be delivered as a live workshop, bootcamp or semester module tailored to your team.
Request this workshop →Go further
I run these tutorials as live, hands-on workshops with datasets, exercises and mentorship tailored to your group.