Introduction to Artificial Intelligence

Introduction to Artificial Intelligence gives you a structured map of the field. Many learners know pieces of AI from news and tools like chatbots, but not how they connect. This course starts with the history and core ideas, then works through the main areas: problem solving and search, knowledge and reasoning, machine learning, neural networks, computer vision, natural language processing and generative AI.

Practical labs in Python let you try each idea: a search algorithm for a puzzle, a classifier on tabular data, a small neural network, a sentiment model and a prompt-driven application built on a language model API. Later modules cover retrieval-augmented generation and AI agents at an introductory level, and responsible AI topics such as bias, privacy, explainability, safety and the evolving regulatory landscape.

There is no external exam. You finish with a capstone and an Assure Success course-completion certificate. The course is a base from which you can choose a specialisation in machine learning, deep learning, generative AI or AI product work.