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the bootcamp

AI Full Stack Bootcamp — Job Ready

Go from building screens to shipping AI features that run in production. Free to read now, and planned to the day.

Enrol freeSee every week
  • Free to follow
  • Every week and day planned, in order
  • Optional tracks to go deeper
  • A new batch every Monday
In ordera fixed route, week by week, planned to the day
One projectSupportDesk grows with you every month
Done whena checklist closes each week, so you know you finished
Proofmilestones and a capstone you can show and link to

What you will be able to do

  1. Build a production backend: Django and FastAPI, SQL, login, background jobs, payments and tests.
  2. Add AI to a product: LLM APIs, structured output, tool calling, RAG, agents and chat interfaces.
  3. Measure and protect it: evals, cost and speed, tracing, and security for AI features.
  4. Deploy it on AWS with Docker, Terraform and CI/CD, then watch it in production.
  5. Finish with a capstone you can show, and prepare for interviews and applications.

Paces and tracks

The roadmap runs at the 6-month pace. Three more paces are coming: you will pick one when you enrol, and it stays fixed.

  • 3monthsMust days onlyComing
  • 6monthsThe coreFirst pace
  • 9monthsThe core, lighter weeksComing
  • 12monthsThe core plus the tracks you pickComing
  • Python trackThe default backend track
    Opens with the app
  • TypeScript / Node trackIts day books are being written
    Opening soon
the six months

Every week, every day

Every week of the six months and its optional tracks, with each day in the order you study it. Open a week to see its days.

Month 1 · Weeks 1–4

Backend foundations

Python, SQL and PostgreSQL, Django and REST APIs, login, permissions and tests.

A multi-tenant API with tests running on GitHub

Month 2 · Weeks 5–8

Production backend

Background jobs, caching, files, payments, async Python and FastAPI, Docker, real-time chat.

A real-time app with logs and metrics

Month 3 · Weeks 9–13

AI engineering, the core

How LLMs work, structured output, tool calling, embeddings, RAG and its quality, AI interfaces.

An AI product with a streaming chat interface

Month 4 · Weeks 14–17 + tracks

AI engineering, advanced

Evals, agents, AI security and reliability, cost, speed and tracing. Tracks: MCP, workflows, fine-tuning.

An agent you can measure, trace and defend

Month 5 · Weeks 18–22 + track

Cloud, DevOps and security

AWS, containers, Terraform and CI/CD, observability and reliability, security.

The product deployed on AWS with infrastructure as code

Month 6 · Weeks 23–26

Capstone and interview preparation

Polish the product and tell its story, interview preparation, a speed project and how to run applications.

A capstone and a job-search plan

Month 1 · Weeks 1–4

Backend foundations

Python, SQL and PostgreSQL, Django and REST APIs, login, permissions and tests.

Milestone A multi-tenant API with tests running on GitHub

  • Week 1Python deep dive
    1. Day 1Tools and core data
    2. Day 2Functions and types
    3. Day 3Classes and the data model
    4. Day 4Generators, decorators, context managers, errors
    5. Day 5Tests, modules and the week project
    6. Day 6Review and reading code
  • Week 2SQL and PostgreSQL
    1. Day 1Setup, basic queries, joins
    2. Day 2Grouping, subqueries, CTEs, window functions
    3. Day 3Data modelling
    4. Day 4Indexes and query speed
    5. Day 5Transactions, locks, PostgreSQL from Python
    6. Day 6Review and mini project
  • Week 3Django and REST APIs
    1. Day 1HTTP from the server side, project setup
    2. Day 2Models and the ORM
    3. Day 3Django REST framework
    4. Day 4API design, service functions, documentation
    5. Day 5Connect the frontend, Django extras
    6. Day 6Review and reading code
  • Week 4Login, permissions, tests and Milestone 1
    1. Day 1How login works
    2. Day 2"Log in with Google" and API keys
    3. Day 3Roles and keeping companies apart
    4. Day 4Testing properly
    5. Day 5Automatic checks, then build
    6. Day 6Milestone 1 and month review
Month 2 · Weeks 5–8

Production backend

Background jobs, caching, files, payments, async Python and FastAPI, Docker, real-time chat.

Milestone A real-time app with logs and metrics

  • Week 5Background jobs, caching, files and payments
    1. Day 1Redis and caching
    2. Day 2Background jobs with Celery
    3. Day 3Files and object storage
    4. Day 4Email and webhooks
    5. Day 5Payments in test mode
    6. Day 6Failure drills and review
  • Week 6Async Python and FastAPI
    1. Day 1Threads, processes and async
    2. Day 2Asyncio in depth
    3. Day 3FastAPI basics
    4. Day 4Database and login in FastAPI
    5. Day 5Streaming, and Django compared with FastAPI
    6. Day 6Review
  • Week 7Docker, Linux and system design basics
    1. Day 1Linux essentials
    2. Day 2Docker
    3. Day 3Docker Compose, reverse proxy, HTTPS
    4. Day 4System design, part 1
    5. Day 5System design, part 2, and reliability patterns
    6. Day 6Review
  • Week 8Real-time chat, observability and Milestone 2
    1. Day 1WebSockets with Django Channels
    2. Day 2Chat widget and agent inbox
    3. Day 3Observability basics
    4. Day 4Speed
    5. Day 5Build day for Milestone 2
    6. Day 6Milestone 2 and month review
Month 3 · Weeks 9–13

AI engineering, the core

How LLMs work, structured output, tool calling, embeddings, RAG and its quality, AI interfaces.

Milestone An AI product with a streaming chat interface

  • Week 9How LLMs work, and the API
    1. Day 1A mental model of LLMs
    2. Day 2First API calls
    3. Day 3Streaming, async, errors, limits
    4. Day 4The model inside a web service
    5. Day 5Prompting basics
    6. Day 6Review
  • Week 10Structured output and tool calling
    1. Day 1Structured output
    2. Day 2Extraction at scale and batches
    3. Day 3Tool calling basics
    4. Day 4Tool design and actions with approval
    5. Day 5Put it into the product
    6. Day 6Review
  • Week 11Embeddings and RAG basics
    1. Day 1Embeddings
    2. Day 2Storing and searching vectors
    3. Day 3The ingestion pipeline
    4. Day 4Retrieval and answer
    5. Day 5Safety between companies, and wiring
    6. Day 6Review
  • Week 12RAG quality
    1. Day 1Measure search properly
    2. Day 2Hybrid search
    3. Day 3Reranking and query rewriting
    4. Day 4Better chunks and context
    5. Day 5Answer quality and conversation
    6. Day 6Review and write-up
  • Week 13AI user interfaces and Milestone 3
    1. Day 1Streaming UI, done right
    2. Day 2Trust and control
    3. Day 3Generative UI and safe integration
    4. Day 4Build Milestone 3 (day 1 of 2)
    5. Day 5Build Milestone 3 (day 2 of 2)
    6. Day 6Milestone, month review, resume
Month 4 · Weeks 14–17 + tracks

AI engineering, advanced

Evals, agents, AI security and reliability, cost, speed and tracing. Tracks: MCP, workflows, fine-tuning.

Milestone An agent you can measure, trace and defend

  • Week 14Evals, measuring AI quality
    1. Day 1Look at the data first
    2. Day 2Build the harness
    3. Day 3The LLM judge, done properly
    4. Day 4Improve with evals, and CI
    5. Day 5Quality in production
    6. Day 6Review and write-up
  • Week 15Agents
    1. Day 1Workflows and agents
    2. Day 2The agent loop and context engineering
    3. Day 3Memory, people in the loop, several agents
    4. Day 4MCP and frameworks
    5. Day 5Testing and hardening the agent
    6. Day 6Review
  • Week 15ATrack A · MCP in depthoptional track
    1. Day 1The protocol and the architecture
    2. Day 2Build a production-style server
    3. Day 3Remote access and login
    4. Day 4The other side, MCP clients and your agent
    5. Day 5Security and tests for MCP
    6. Day 6Review and the new parts
  • Week 16Security and reliability of AI features
    1. Day 1Prompt injection and the threat model
    2. Day 2Defences that work
    3. Day 3Privacy and data handling
    4. Day 4Reliable model calls
    5. Day 5Abuse, cost limits and responsibility
    6. Day 6Review
  • Week 17Cost, speed, tracing, other providers and Milestone 4
    1. Day 1Tracing AI requests
    2. Day 2Cost and speed
    3. Day 3Other providers and gateways
    4. Day 4Open models, fine-tuning, images
    5. Day 5Build Milestone 4
    6. Day 6Milestone, month review, first applications
  • Week 17ATrack B · AI workflows and durable orchestrationoptional track
    1. Day 1Think in workflows
    2. Day 2Build with a graph framework
    3. Day 3Make it durable
    4. Day 4Triggers, integrations and low-code
    5. Day 5Test and run it
    6. Day 6Review
  • Week 17BTrack C · Making models yours (practical fine-tuning)optional track
    1. Day 1Decide, and prepare the data
    2. Day 2Set up and train
    3. Day 3Evaluate honestly
    4. Day 4Serve it and wire it in
    5. Day 5Other ways to customise, and the limits
    6. Day 6Write it down
Month 5 · Weeks 18–22 + track

Cloud, DevOps and security

AWS, containers, Terraform and CI/CD, observability and reliability, security.

Milestone The product deployed on AWS with infrastructure as code

  • Week 18AWS foundations
    1. Day 1Account safety and IAM
    2. Day 2Networking
    3. Day 3Servers and file storage
    4. Day 4Deploy version 0, one server done properly
    5. Day 5The AWS library, a taste of serverless, and cost
    6. Day 6Review
  • Week 19Containers and managed services on AWS
    1. Day 1Managed database
    2. Day 2Containers behind a load balancer
    3. Day 3Supporting services
    4. Day 4Scaling and staying up
    5. Day 5Bedrock and an architecture review
    6. Day 6Review
  • Week 20Terraform and CI/CD
    1. Day 1Terraform basics
    2. Day 2Terraform for the whole setup
    3. Day 3The checking part of the pipeline (CI)
    4. Day 4The deploying part of the pipeline (CD)
    5. Day 5Daily working comfort and release routine
    6. Day 6Review
  • Week 21Observability and reliability in production
    1. Day 1Logs, metrics and traces on AWS
    2. Day 2Reliability targets and alerts
    3. Day 3Incidents, runbooks and reviews
    4. Day 4Backups and disaster recovery
    5. Day 5Cost and capacity
    6. Day 6Review
  • Week 22Security and Milestone 5
    1. Day 1Attack, to learn
    2. Day 2Defend your stack
    3. Day 3Dependencies and automatic scanning
    4. Day 4Threat model, AWS baseline, reviewing AI-written code
    5. Day 5Milestone 5 and month review (day 1 of 2)
    6. Day 6Milestone 5 and month review (day 2 of 2)
  • Week 22ATrack D · Multimodal, voice, computer use and staying currentoptional track
    1. Day 1Images and documents
    2. Day 2Voice
    3. Day 3Computer use and browser agents
    4. Day 4AI coding agents, as a power user
    5. Day 5Staying current, as a system
    6. Day 6Review
Month 6 · Weeks 23–26

Capstone and interview preparation

Polish the product and tell its story, interview preparation, a speed project and how to run applications.

Milestone A capstone and a job-search plan

  • Week 23Polish the product and tell its story
    1. Day 1Product polish
    2. Day 2Product thinking
    3. Day 3Documentation and code quality
    4. Day 4Case studies and the final video
    5. Day 5Portfolio, profiles, resume
    6. Day 6Practise the story
  • Week 24Interview preparation
    1. Day 1Fundamentals
    2. Day 2Classic system design
    3. Day 3AI system design and AI questions
    4. Day 4Practical formats
    5. Day 5Behavioural questions and your story
    6. Day 6The full practice loop
  • Week 25Speed project and applications
    1. Day 1Spec and skeleton
    2. Day 2Build with the agent (day 1 of 3)
    3. Day 3Build with the agent (day 2 of 3)
    4. Day 4Build with the agent (day 3 of 3)
    5. Day 5Ship
    6. Day 6Review
  • Week 26Interviews and next steps
    1. Day 1Interview day (day 1 of 4)
    2. Day 2Interview day (day 2 of 4)
    3. Day 3Interview day (day 3 of 4)
    4. Day 4Interview day (day 4 of 4)
    5. Day 5The six-month review
    6. Day 6The next 90 days
what you will build

One real product: SupportDesk

A customer support tool that companies sign up for. You build one product across all six months. One deep project, built across all six months, gives you one product you can show and explain.

What it does

  1. A company uploads its help documents.
  2. The company puts a small chat widget on its website.
  3. A visitor asks a question in the widget.
  4. An AI assistant answers from the help documents and shows its sources.
  5. If the AI is not sure, it hands the chat to a human support agent.
  6. The human agent gets AI help: suggested replies, summaries, and actions the AI can prepare for approval.

What works at each milestone

  • W4
    1. Core APICompanies, users, roles, tickets, conversations. Login. Tests. A simple web screen.
  • W8
    2. HelpdeskLive chat between widget and inbox. File uploads. Emails. Billing in test mode. Runs in Docker.
  • W13
    3. AI answersDocument upload and search. AI answers with sources. Handoff to a human. AI help for agents.
  • W17
    4. AI agentTools with human approval. Quality tests (evals). Safety checks. Cost and speed dashboards.
  • W22
    5. ProductionLive on AWS. Automatic deploys. Monitoring and alerts. Security review.
  • W23
    PolishDemo mode, documentation, case studies.
how it works

From sign-up to SupportDesk in four steps

01

Enrol

Make a free account and press Enrol. Every week of the roadmap is open to read.

02

Start on a Monday

A new batch starts every Monday. Until you start, read ahead at your own speed.

03

Follow it day by day

Each day says what to learn and what to do. When the app opens, add the weeks to your study plan and finished days are counted for you.

04

Build, then show it

Build SupportDesk milestone by milestone: one product you can link to. A certificate for finishers is coming.

This is for you if

  • You can already build a frontend and want to own the whole stack.
  • You want AI engineering skills, learned in a fixed order.
  • You can give about 40 hours a week for six months.

This is not for you if

  • You have never written code. Start with a beginner course first.
  • You want a job guarantee. Nobody can promise that, and this roadmap does not.

Frequently asked questions

The bootcamp: time, pace, cost and what it can and cannot promise.

Want to ask something else? Write to us

Is it really free?

Yes. The roadmap, the courses and the cheatsheets are free to read now. Following the roadmap in the app is free with an account; the study planner and quizzes are free too when they open. Day books and handbooks are optional and paid.

When does it start?

A new batch starts every Monday. You can enrol now and read every week of the roadmap before you start.

How much time does it take?

The plan is written for about 40 hours a week over six months, plus optional track weeks. If you cannot give that, the study planner (coming with the app) will move your dates as you fall behind. Fixed slower and faster paces are coming.

What if I fall behind?

The plan keeps its order on a bad week. Once the app opens, days you miss stay in your study plan and can be rescheduled; nothing expires.

Can I go faster or slower?

Not yet. The roadmap runs at the 6-month pace. Paces of 3, 9 and 12 months are coming; you will choose one when you enrol, and it stays fixed.

Do I need the day books?

No. Every day is planned on the roadmap for free. A day book is the same day as a print-ready book, for people who like to learn on paper.

Will it get me a job?

It gives you skills and proof of work. It cannot promise a job on a fixed date, because hiring depends on the market, your location and your past work.

Start the bootcamp

Go from building screens to shipping AI features that run in production. A new batch starts every Monday.

Enrol freeDay books in the Store
The study planner dashboard: today’s sessions with revision first, progress per subject and the focus timer