GenAI Architect
Bootcamp
A project-based learning path to design, build, secure, deploy, and operate production-ready Generative AI solutions.
Learning Roadmap
Move through 10 focused phases from fundamentals to interview-ready architecture mastery.
Foundations
Understand AI, ML, deep learning, GenAI, LLMs, embeddings, and the architecture vocabulary.
Prompt Engineering
Design instructions, roles, examples, guardrails, and reusable prompt patterns for real apps.
RAG Architecture
Build grounded retrieval systems with chunking, vector databases, citations, and evaluation.
Agentic AI
Plan tool calling, memory, orchestration, human review, and multi-step reasoning workflows.
Security
Protect data, prompts, tools, model outputs, access paths, and production AI workflows.
Python Development
Implement APIs, services, evaluation scripts, and GenAI integrations with Python.
GitHub & CI/CD
Version, test, review, and release GenAI applications with practical delivery workflows.
Docker & Kubernetes
Containerize services, deploy workloads, and reason about scalable cloud-native operations.
Production GenAI
Operate with monitoring, cost controls, fallback paths, observability, and reliability checks.
Interview Mastery
Practice architecture decisions, scenario questions, tradeoffs, and production design reviews.
Ready to start the bootcamp?
Begin with the first module, then work through the roadmap toward production GenAI architecture and interview mastery.
Start Module 1