Applied AI Live
A 3-month weekend live cohort for professionals and builders who want to ship real AI systems, not just follow tutorials. Agents, RAG, automation, and a capstone you can put on your resume.
Apply for the CohortWhat will you learn in 3 months?
Every module combines live instruction, coding sessions, and a tangible deliverable you can add to your portfolio.
LLMs, Prompting & the AI Dev Stack
- Understand transformer fundamentals, tokens, context windows, and model selection
- Master advanced prompting: chain-of-thought, few-shot, role-based, and structured outputs
- Set up a modern Python development environment for AI projects
- Compare OpenAI, Anthropic, and open-source models for real tasks
APIs, Embeddings & Vector Search
- Call OpenAI and Anthropic APIs securely with retries, streaming, and error handling
- Generate and compare text embeddings for semantic similarity
- Store and query vectors with Chroma, FAISS, and Pinecone
- Build a semantic search engine over your own documents
Retrieval-Augmented Generation (RAG)
- Chunk, embed, and index documents for production-grade retrieval
- Build a full RAG pipeline with re-ranking and source attribution
- Evaluate retrieval quality and reduce hallucinations with grounding
- Deploy a RAG-backed Q&A app with a simple web interface
Custom Chatbots & Conversational UI
- Design chatbots with memory, context management, and user intent parsing
- Build a Streamlit or Gradio frontend for interactive demos
- Implement system prompts, guardrails, and persona design
- Package your chatbot as a shareable prototype
AI Agents & Tool Use
- Design agents that reason, plan, and call external tools
- Connect LLMs to calculators, APIs, databases, and search engines
- Build a ReAct-style agent from scratch and with LangChain agents
- Handle tool failures, retries, and ambiguous user requests
LangChain, LangGraph & Orchestration
- Chain prompts, models, and parsers with LangChain Expression Language
- Model multi-step workflows as state machines with LangGraph
- Build conditional loops, human-in-the-loop checkpoints, and parallel branches
- Trace and debug agent runs with LangSmith
No-Code / Low-Code Automation
- Automate business workflows with Make.com and n8n
- Trigger AI actions from spreadsheets, emails, forms, and CRMs
- Build a lead-qualification or content-publishing pipeline
- Integrate no-code frontends with AI backends via webhooks
Voice, Vision & Multimodal AI
- Process images with vision models for extraction, classification, and OCR
- Build voice agents with speech-to-text, LLM reasoning, and text-to-speech
- Create a document parser that combines PDF text, tables, and images
- Deploy a multimodal assistant for customer support or operations
Evaluation, Observability & Safety
- Benchmark LLM outputs with deterministic and model-based evals
- Monitor latency, cost, token usage, and error rates in production
- Add guardrails, PII filtering, and content moderation
- Set up logging and tracing for continuous improvement
Deployment & Productionizing Apps
- Containerize and deploy AI apps with FastAPI, Docker, and cloud platforms
- Build async job queues for long-running generation tasks
- Manage secrets, environment configs, and API rate limits
- Publish a live app with a public URL and basic authentication
Capstone Project Sprint
- Choose a real-world problem: internal copilot, support agent, or automation suite
- Architect the solution end-to-end with your mentor's feedback
- Ship a working MVP with code, documentation, and demo video
- Prepare your project for portfolio and interviews
Demo Day, Career Prep & Next Steps
- Present your capstone to peers and mentors for live feedback
- Refine your resume, GitHub, and LinkedIn for AI engineering roles
- Practice mock interviews for AI engineer and product positions
- Join the alumni network and ongoing project opportunities
What will you be able to do?
By the end of the cohort, you won't just understand AI. You'll have shipped with it.
Design, evaluate, and deploy retrieval pipelines that ground LLMs in real company data.
Create goal-driven agents with tool use, memory, and multi-step reasoning using LangChain and LangGraph.
Add LLM features to web apps, automate internal workflows, and build AI-powered user experiences.
Deploy, monitor, and iterate on AI systems with the workflows used by top engineering teams.
Walk away with shipped code, demos, and documentation you can show in interviews and on GitHub.
Make informed trade-offs between cost, latency, accuracy, and privacy for any AI use case.
Who is this program for?
This cohort is designed for people who want to go from "AI curious" to "AI capable."
Which tools will you use?
We focus on tools that are in demand right now, and that you'll keep using after the cohort.
What does it cost?
One published price. It covers live instruction, mentorship, and the four projects you ship. EMI options available.
- 36+ hours of live instruction
- 4 real-world portfolio projects
- Weekly 1:1 mentor checkpoints
- Private community & alumni access
- Certificate of completion
- Interview & resume support
Questions? Answered.
We run 2 to 3 live sessions per week, mostly on weekday evenings or weekends to accommodate working professionals. Each session is 2 to 3 hours with hands-on coding and Q&A. Recordings are shared within 24 hours.
You should be comfortable with basic programming (any language). Familiarity with Python is helpful but not mandatory; we cover the essentials in Week 1. A laptop, stable internet, and curiosity are required.
Yes. Everyone who completes the program and submits the capstone project receives a verified certificate of completion from Rewire.
Full refund within 7 days of the cohort start date if you attend all sessions and feel the program isn't right for you. See our Refund Policy for full terms.
Applied AI Live is fully live and interactive. You code alongside the instructor, ask questions in real time, and get feedback on your projects during live reviews.
Ready to build with AI?
Batches are deliberately small, so every project gets mentor feedback.
Apply for the Cohort