Generative AI — Schedule
Week-by-week schedule of Generative AI.
The operational schedule for Generative AI. Per-cohort dates fill in at intake; the structure below is stable across cohorts.
The single source of truth is _data/ia-generative.yml. Edits there flow through this page automatically.
| Week | Title | Pitch | Detail |
|---|---|---|---|
| 01 | Foundations of Language Models | What a language model is, what it isn't, and why ChatGPT was the convergence of three decade-long research programs. | week 01 → |
| 02 | The Transformer Architecture | Vaswani et al. 2017 in eight pages — and what every successor since has changed about it. | week 02 → |
| 03 | GPT and Text Generation | The GPT family from 2018's 117M-parameter GPT-1 to today's trillion-parameter frontier, plus the inference-time engineering that makes deployment feasible. | week 03 → |
| 04 | Prompt Engineering | The prompt as a programming surface. The standard patterns, the diagnostic techniques for failing prompts, and the management practices that survive production. | week 04 → |
| 05 | Fine-Tuning LLMs | Adapting a pretrained model to a domain or a task. LoRA, QLoRA, and the parameter-efficient fine-tuning revolution. | week 05 → |
| 06 | Retrieval-Augmented Generation | Don't make the model memorize everything — let it look things up. The dominant production pattern for grounded LLM applications. | week 06 → |
| 07 | Diffusion Models and Image Generation | Diffusion models for image generation: DDPM's denoising principle, latent diffusion (the engine behind Stable Diffusion), and how the conditional architectures of 2026 build on both. | week 07 → |
| 08 | Evaluation, Safety, and Alignment | How do you know your generative model is actually good? Spoiler: we don't entirely. | week 08 → |
| 09 | LLM Agents and Tool Use | The model as an orchestrator: it plans, calls tools, observes results, iterates. | week 09 → |
| 10 | Final capstone — build and deploy a generative system | Each participant ships a RAG system, a fine-tuned domain model, or a multi-step agent. Live demo. Public repository. Technical writeup. | week 10 → |
Operational notes
- Default timezone: Africa/Lagos (UTC+1). Per-cohort timing negotiated at intake.
- Lab notebooks and problem-set repos live in the cohort GitHub organization.
- The bilingual lecture notes remain the reference text.