Applied Machine Learning and Agentic AI: Fundamentals to Next Generation Artificial Intelligence

Python is the language of modern AI, and this module takes you from a blank Google Colab notebook to writing clean, working code. You will cover core syntax, control flow and functions before moving to NumPy for numerical computing and Pandas for working with real datasets, finishing with AI-assisted development so you can use coding assistants well rather than blindly.

Every dependable model starts with understanding the data. This module builds the exploratory data analysis and visualization skills that let you find patterns, test assumptions and spot problems before they reach a model, closing with a full case study taking one dataset from raw file to clear insight.

Classical algorithms remain the backbone of applied machine learning and the clearest way to learn how models actually work. You will build regression and classification models, work through tree-based methods, and cover both partitional and hierarchical clustering, with a case study tying prediction and evaluation together.

This module opens up the neural network. You will work through architecture and backpropagation, learn the optimization techniques that make training stable, then move to the convolutional and recurrent models behind computer vision and sequence learning, plus autoencoders for representation learning.

Transformers underpin almost everything in current AI. You will study the architecture in depth, see how it extends to vision and audio, then move into large language models and generative AI across text, image and video, finishing with the newest LLM designs including reasoning models and Mixture of Experts.

A model only creates value once it runs in production. This module covers deploying models with Hugging Face and serving them efficiently with vLLM, working with LLM APIs and the parameters that shape their output, and analysing the cost and infrastructure trade-offs behind any real deployment.

The newest addition to the programme, and the reason for its new title. Agentic AI covers systems that reason, retrieve and act rather than simply generate text. You will learn practical prompt engineering, build retrieval-augmented generation knowledge systems over your own data with LangChain, and work with the tooling used to assemble AI agents, currently the fastest-growing skill area in applied AI.