Build & Deploy AI Applications in 8 Weeks
Design, build, and deploy LLM-based applications with real-world use cases and AWS integration.
- Weekly live sessions
- Full tuition: $6,000
- 100% Remote
How the Bootcamp Works
Weekly CORE Sessions
Hands-on AI system building
Mondays, 2 p.m. PT
Office Hours
Commercial use case talks
Thursdays, 2 p.m. PT
AMA Sessions
Learn from industry experts
Thursdays, 2 p.m. PT
Capstone Project
Your Al Portfolio Centerpiece
Meet your instructors
Ed Donner
Nebula
With a background in LLM deployment and multi-agent AI workflows, Ed brings deep real-world expertise from both startups and enterprise tech leadership.
What you’ll learn
- Build production-ready AI applications using cutting edge tools.
- Design and evaluate prompts to power intelligent agents and copilots.
- Deploy your AI systems to the cloud with scalable infrastructure.
- Master embeddings and vector databases for retrieval-augmented generation (RAG).
- Set up automated workflows for orchestration, chaining, and agent behavior.
- Monitor, secure, and optimize your apps for performance and cost efficiency.
- Create a full-stack capstone project to showcase your AI engineering skills.
Curriculum Overview
Part 1: Core AI Engineering Skills
Week 1
Ed Donner
- 01. Set up your AI engineering environment: Cursor, GitHub, UV
- 02. Python & API refresher for AI Engineers
- 03. Explore and compare 12 different chat V.S. reasoning LLM
- 04. Build your first LLM-powered app using Gradio and DALL-E
Weeks 2
LLM Behaviour Design
- 01. Learn to control tone, structure, and style using prompt engineering
- 02. Build a multi-turn coaching assistant with LangChain & Gradio
- 03. Introduction to LangChain PromptTemplates and OutputParsers
- 04. Design structured outputs for reliability and reuse
Weeks 3
Retrieval-Augmented Generation (RAG)
- 01. Create a RAG pipeline using Chroma and OpenAI embeddings
- 02. Chunking strategies and vector similarity search
- 03. Introduction to hierarchical RAG and when to use it
- 04. Inject retrieved content into LLM prompts for grounded answers
- 04. Explore chunking strategies and their impact on accuracy
Weeks 4
Agentic AI Foundations
- 01. Build your first tool-using agent with LangChain
- 02. Create a Digital Twin that reflects your voice and style
- 03. Chain together tools, RAG, and memory for task execution
- 04. Debugging: agent reasoning and tool routing behavior
Part 2: production-ready Deployment
Week 5
Production Readiness & Deployment
- 01. Modular agent logic using LangChain Runnables
- 02. Python & API refresher for AI Engineers
- 03. Explore and compare 12 different chat V.S. reasoning LLM
- 04. Build your first LLM-powered app using Gradio and DALL-E
Week 6
Memory & Security
- 01. Implement long- and short-term memory using LangChain and Chroma
- 02. Apply the Model Context Protocol (MCP) to organize memory pipelines
- 03. Ethical hacking of your agent via prompt injection
- 04. Business rules through post-prompt tool call validation
- 05. Summarize conversations to fit memory within token limits
- 06. Designing secure, memory-aware agents that avoid silent failures
Week 7
Using RAG in Production
- 01. Enhanced retrieval with query rewriting and reranking
- 02. Logging failed lookups to identify knowledge gaps
- 03. Private knowledge base for your Digital Twin
- 04. Extend your agent’s domain knowledge using RAG
- 05. Compare and tune retrieval with Chroma, Pinecone, and Weaviate
Week 8
Capstone Project
- 01. Deploy your final Digital Twin agent to AWS
- 02. Log unanswered questions and send Push Notifications to provide missing info
- 03. Embed new knowledge and update the agent’s memory dynamically
- 04. LangSmith to evaluate agent behavior and log tool use
- 05. Present production-ready agents and share takeaways
Tools you’ll use
Guest AMA speakers
Luka Anicin
AI Consultant & Advisor
Google Developers Expert
Jon Krohn
AI Author & Speaker
SDS, Podcast Host
Rico Meinl
AI Engineer & Strategist
Retro, Applied AI Specialist
Laurent Mathieu
Cybersecurity Expert
AWS, Instructor Freelancer
Ayobami Ayodeji
Kubernetes & DevOps Expert
Microsoft, Senior Technical PM
Sinan Ozdemir
LLM Expert & Author
Founder, CTO
4+ industry guests over the 8 weeks
*AMA guests may change by cohort. Exact number of AMAs is not guaranteed.
Where our students work
Earn Recognition for Your Skills
At the end of the 8-week bootcamp, you’ll receive an official certificate you can proudly showcase on LinkedIn and include in job applications to stand out in a competitive job market.
What you’ll get
- 🎯 8 weeks of live, expert-led training
- 💡 3-hour weekly CORE session
- 💼 2-hour weekly Office Hours
- 🚀 Stretch assignments to go further
- 🎤 4+ live AMAs with industry experts
- 🧠 Master RAG, memory & orchestration
- 🤖 Build production-ready AI agents
- 🤝 Breakout sessions in small teams
- 💬 Exclusive Slack support & networking
- 📈 Discuss trends & AI developments
- 🎥 Lifetime access to recordings
- ⬇️ Access all code, templates & workflows
- 🏆 Capstone project with expert feedback
- 🎓 Completion Certificate & Linked-In Badge
Total Program Cost: $6,000
Secure your seat with a $100 refundable deposit.
Student Success Stories
What made you decide to join the Bootcamp?
Saravanan S.
Bootcamp participant
What were your concerns going in?
Ryan B.
Bootcamp participant
How would you rate the quality of instructors and materials?
Georgian P.
Bootcamp participant
How did it boost your skills and confidence?
Harish C.
Bootcamp participant
Would you recommend this program to others and why?
Blake L.
Bootcamp participant
Have you seen any tangible results since completing the bootcamp?
Pratik R.
Bootcamp participant
Reserve Your Spot – Only 10 Seats Per Cohort
Reserve Your Spot
Frequently Asked Questions
Who is this Bootcamp for?
AI engineers, developers, and tech professionals who want to go from intermediate to advanced level and design, build, and deploy production-ready AI applications.
Do I need prior AI / Cloud experience?
Basic Python skills (at least 6 months experience) and AWS fundamentals (understanding of EC2, S3, IAM) are required. No prior AI engineering experience is necessary, we’ll teach you everything else.
How much does it cost?
The full Bootcamp fee is $6,000. You can secure your spot today with a $100 deposit, and pay the balance before the start date. Seats are limited, so early registration guarantees your place in the next cohort.
What’s required time commitment?
8 weeks of live sessions, approx. 5-7 hours per week including CORE sessions, office hours, and in some weeks also AMA’s. Plus, at least 4-8 more hours each week of self-study and assignments.
Will I work on real projects?
Yes — you’ll build multiple AI systems, culminating in a production-ready capstone project.
Can I access the recordings later?
Yes — you get lifetime access to all recordings, code, and resources.
Is it 100% online?
Yes — all sessions are live online, and you can join from anywhere in the world. Sessions times work best for ET, PT and AEST timezones.
Do I get a certificate?
A deployed AI project, a completion certificate, and the skills to launch production-ready AI apps.