This hub is a central place for learning about Generative AI, based on a single course offered under two codes (DV1712 and DV1729). The course provides a clear, step‑by‑step introduction to generative AI, beginning with machine learning fundamentals and progressing through model training, deployment, and practical applications. Students work hands‑on with modern AI systems to generate text, images, code, and other types of media.

The course accommodates learners of all backgrounds with two parallel tracks: one for those with programming experience and one for non‑programmers. Each track balances theoretical lectures with guided exercises. By the end of the course, students gain a solid understanding of generative AI concepts and the skills needed to experiment with, fine‑tune, and deploy models from large language models (LLMs) to diffusion and multimodal systems.

Key topics include:

Fundamentals of Generative AI: core concepts, neural networks, and machine learning foundations
Probability & Language Modeling: N‑gram methods and probabilistic approaches to text generation
Model Architectures: from feedforward and convolutional networks to transformer-based designs
Core Mechanisms: tokenization, embeddings, attention, and positional encoding
Generative Paradigms: auto-regressive vs. diffusion methods for text and image synthesis
Agentic AI Workflows: designing and orchestrating AI agents for multi-step task automation
Tools & Frameworks: practical use of programming environments, libraries, and interfaces
Fine‑Tuning & Adaptation: techniques for tailoring models to specific tasks and domains
Deployment & Operations: containerization, API development, monitoring, and lifecycle management
Applied Domains: text, media, code, data generation; integration with robotics and vision-language systems
Case Studies & Ethics: real-world examples, evaluation metrics, bias mitigation, and user experience enhancements

Slack Workspace (join for discussions):

https://join.slack.com/t/generativeair-9m42318/shared_invite/zt-365favbbn-34ACFAW55aciROMpNPMJ~g

Zoom room (lectures and meeting):

https://bth.zoom.us/j/62895269069

Recorded Sessions:

Sessions

Recommended Materials:
Materials

General Concepts
Transformers and Large Language Models
Vision (Language) Models and Robots
Tools & Programming
References
Other