Project Group

Artificial Intelligence Projects

Project work in artificial intelligence covering the history and concepts of AI, regression and classification foundations, neural networks, reinforcement learning, and the wider ethical and practical context of intelligent systems.

Reinforcement Learning Work

One of the clearest practical AI pieces is a snake-playing agent built with a compact Q-network, replay memory, helper functions, and iterative self-play. The project folders include both manual game versions and training versions, showing the progression from environment setup to agent training and model saving.

Broader AI Scope

The wider module content moved through the history of AI, core concepts, regression, classification, deep learning, CNN-related material, intelligent agents, reinforcement learning, and later social and ethical questions about AI in modern society.

Themes

Areas Covered

Agent behavior, environment state design, reward logic, and self-play training loops.
Regression, classification, neural networks, and reinforcement learning as linked parts of the same AI learning path.
Practical implementation of AI ideas in Python, notebooks, transcripts, figures, and assignment writeups.

Module Path

From Theory To Systems

The underlying module folders show a full progression rather than a single AI demo: lecture material on the Turing Test and core AI concepts, hands-on notebook work for regression and classification, neural-network examples on tabular data, and then reinforcement-learning material that moves from a manual snake game toward a trainable agent. That combination is what this page is intended to represent.