Master the end-to-end workflow for building, tuning, and deploying AI copilots. This immersive 6-week journey blends the theory of Large Language Models with hands-on labs, curated tools, and production best practices designed for working professionals.
The program is crafted for developers, data scientists, and solution architects who want to move from consuming AI APIs to creating enterprise-grade AI assistants. We start with essential Python refreshers, progress through transformer foundations, and rapidly move into prompt engineering, retrieval augmented generation, guardrails, and deployment on cloud infrastructure. Every week alternates between concept briefings, guided labs, and product-building sprints to ensure depth and confidence.
Refresh the core Python skills that power the rest of the journey and set up an efficient AI tooling stack.
Dive into transformers, tokenization, and evaluation techniques to reason about LLM behaviour.
Create predictable agents with system prompts, guardrails, and evaluation frameworks.
Fuse proprietary knowledge bases with LLM reasoning to answer domain questions with citations.
Compose multi-step AI workflows that call tools, orchestrate APIs, and manage conversations.
Harden your AI product with CI/CD, observability, and financial guardrails.
Assignments are intentionally progressive—each deliverable feeds the final production-ready AI assistant.
Kick-off call, environment setup, Python refresher, and OpenAI quick wins.
Design review of prompt strategies and responsible AI guidelines; iterate on RAG plan.
Integrate monitoring, caching, and testing pipelines before final deployment sprint.
