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NOW TAKING ENQUIRIESTalk through your starting point, timing and fees

START WITH THE FOUNDATIONS · BUILD WITH GUIDANCE

Python, Cloud &
AI Engineering.

Start with your first Python program. Build applications, run them on AWS and grow into document-based AI and controlled agents—with practice and review along the way.

THE LEARNING PLAN / WEEK BY WEEK

See the next step.
Understand why it matters.

Every week gives you a goal, practical work and something to discuss. Open a week to see the detail. Projects develop as your skills grow.

This is a suggested weekly learning sequence. Your starting point and practice may change the pace. Talk with us about the teaching schedule, time commitment and support before joining.

01

Weeks 1–8 / Start here

Python Foundations

Learn to write Python programs and use them to process files and automate everyday tasks.

Starting requirements, topics & tools

Before you startBasic computer skills. No previous coding experience is needed.

  • Write your first programs

    Use variables, conditions and loops. Read what your code does, one step at a time.

  • Work with data

    Use lists and dictionaries, and read and write text and CSV files.

  • Organise your code

    Break a problem into functions and reuse them in a small program.

  • Find and fix mistakes

    Read error messages, handle missing inputs and check the result with simple tests.

Tools & conceptsPython / Code editor / Git

WEEK
01
Your first Python program

This week's goal

Get comfortable with files, folders, the editor, running Python and asking a precise question.

Your practical work

Run and change a first program. Explain how you opened, changed and ran it; bring one point of confusion.

Let's talk through it

How would you change the message and run the program again?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
A tool that collects and cleans data for you
WEEK
02
Values, inputs and calculations

This week's goal

Use values, variables, text, numbers and input.

Your practical work

Build a small calculator or conversion task; explain the calculation and test ordinary inputs.

Let's talk through it

Which inputs would produce a surprising result?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
A tool that collects and cleans data for you
WEEK
03
Make a decision with code

This week's goal

Make decisions with conditions and comparisons.

Your practical work

Build a rule-based checker. Discuss valid, invalid and boundary examples in plain language.

Let's talk through it

What happens exactly at the boundary between two rules?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
A tool that collects and cleans data for you
WEEK
04
Work through a set of records

This week's goal

Repeat work with loops, lists and dictionaries.

Your practical work

Summarise a small set of records; trace one iteration and fix a mistake together.

Let's talk through it

Can you trace what changes during one loop?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
A tool that collects and cleans data for you
WEEK
05
Break a problem into functions

This week's goal

Break work into functions and readable steps.

Your practical work

Start Project 1. Write separate steps for reading, checking and summarising data.

Let's talk through it

Can someone understand each function from its name and inputs?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
A tool that collects and cleans data for you
WEEK
06
Files, errors and missing data

This week's goal

Read and write files; handle errors and unexpected values.

Your practical work

Run Project 1 on an incomplete CSV file. Explain which records need attention and why.

Let's talk through it

What does your program do with a missing or invalid record?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
A tool that collects and cleans data for you
WEEK
07
Tests and your first GitHub change

This week's goal

Check behaviour with simple tests; introduce Git and a small GitHub change.

Your practical work

Add test cases and save a readable change history. Discuss what the tests do and do not check.

Let's talk through it

Which mistake would your tests catch, and which would they miss?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
A tool that collects and cleans data for you
WEEK
08
Project 1: review, revise, explain

This week's goal

Consolidate the foundation through review and revision.

Your practical work

Demonstrate Project 1, respond to a changed requirement and explain the solution without reading a script.

Let's talk through it

Can you change one requirement and explain the revised result?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
A tool that collects and cleans data for you
02

Weeks 9–12 / Build on the basics

Advanced Python

Organise larger Python programs so they are easier to test, extend and maintain.

Starting requirements, topics & tools

Before you startYou can write functions and work with lists, dictionaries and files.

  • Structure an application

    Separate responsibilities into modules and packages so changes stay manageable.

  • Model the problem

    Use classes and composition when they make the program easier to understand.

  • Handle growing amounts of data

    Use iterators and generators, and understand when to process data a piece at a time.

  • Improve existing code

    Write tests, debug unexpected behaviour and simplify code while preserving what it does.

Tools & conceptsPython / Git / Automated tests

WEEK
09
Give your application a structure

This week's goal

Structure code into modules with a repeatable environment.

Your practical work

Refactor Project 1 and write setup instructions that another person can follow.

Let's talk through it

Could someone follow your setup notes without your help?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
A tool that collects and cleans data for you
WEEK
10
Model a problem with classes

This week's goal

Understand classes and composition through a concrete problem.

Your practical work

Model a small workflow; compare the class-based approach with simpler functions.

Let's talk through it

Why did you choose a class here? Would functions be simpler?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
A tool that collects and cleans data for you
WEEK
11
Process data and investigate mistakes

This week's goal

Process larger inputs with iterators and generators; debug methodically.

Your practical work

Change the data-processing approach and explain the behaviour on an empty or large input.

Let's talk through it

How would you locate the cause of a wrong result?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
A tool that collects and cleans data for you
WEEK
12
A task, a change and a review

This week's goal

Make a change through a ticket, branch, pull request and review.

Your practical work

Introduce Jira and Confluence through one change. Revise after feedback and explain why the tests still pass.

Let's talk through it

What changed after review, and how did you check it?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
A tool that collects and cleans data for you
03

Weeks 13–16 / After Python foundations

Web Scraping & Automation

Collect information from sources you are allowed to use, and turn a repetitive manual job into a program that runs on its own.

Starting requirements, topics & tools

Before you startYou can write functions, work with files and read a Python error message.

  • See how a page is put together

    Understand the request your program sends, the response that comes back and the HTML behind the page you read on screen.

  • Collect only what you are permitted to

    Check a source's terms and robots rules, identify your requests honestly and keep them to a polite rate. Getting past a login, paywall or CAPTCHA is not taught here.

  • Automate a job you do by hand

    Fetch, extract, check and save a result, so a routine that took an hour each week runs by itself.

  • Keep it running

    Handle a page that changed, a request that failed and a run that must repeat on a schedule with a log you can read.

Tools & conceptsPython / HTTP / HTML / Scheduled runs

WEEK
13
How a web page is put together

This week's goal

Understand HTTP requests and responses, and the HTML structure behind a page you can read on screen.

Your practical work

Fetch a permitted practice page and pull out the few values that matter. Explain what your request asked for and what came back.

Let's talk through it

What did the server actually send back, and which part of the page did you need?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
A tool that collects and cleans data for you
WEEK
14
Collect data responsibly

This week's goal

Check what a source permits, identify your requests honestly and keep them to a polite rate.

Your practical work

Read the terms and robots rules for a practice source, set a sensible rate limit and record what you are allowed to collect. Ways of getting past a login, paywall or CAPTCHA are not taught here.

Let's talk through it

What does this source allow, and how would you show that your program respected it?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
A tool that collects and cleans data for you
WEEK
15
Automate a job you do by hand

This week's goal

Turn a repetitive manual routine into a program that fetches, checks and saves the result.

Your practical work

Extend Project 1 so it collects its own input instead of being handed a file. Validate each record before saving it.

Let's talk through it

Which step used to be manual, and what does your program do when the data looks wrong?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
A tool that collects and cleans data for you
WEEK
16
Make it run without you

This week's goal

Handle failures, changes and repeated runs on a schedule.

Your practical work

Add retries, a readable run log and a scheduled run. Change the source deliberately and show what your program does.

Let's talk through it

The page changed and a run failed. How would you find out, and what would you fix first?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
A tool that collects and cleans data for you
04

Weeks 17–20 / After Python

APIs & Integrations

Build an API and connect your Python application to other services. An API is a way for applications to exchange information.

Starting requirements, topics & tools

Before you startComfort with Python functions, data structures and error handling.

  • Understand requests and responses

    Read HTTP methods, status codes and JSON data.

  • Build a useful interface

    Define endpoints, validate inputs and return clear responses.

  • Connect another service

    Use authentication and configuration without putting credentials in your code.

  • Handle failed requests

    Work through timeouts, unavailable services and errors the caller needs to understand.

Tools & conceptsPython / HTTP / JSON / SQL / Database foundations / API testing

WEEK
17
Build your first API

This week's goal

Understand HTTP, JSON, requests and responses.

Your practical work

Start Project 2 with a small Python API and explain what each endpoint accepts and returns.

Let's talk through it

What does the caller send, and what does your API return?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An application you can build, run and improve
WEEK
18
Store and query application data

This week's goal

Model simple stored data and use basic SQL.

Your practical work

Save and query application records. Explain tables, identifiers, missing records and a simple relationship.

Let's talk through it

How do the records relate, and what if one is missing?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An application you can build, run and improve
WEEK
19
Connect services and handle failure

This week's goal

Validate inputs and connect a second service with controlled credentials and failure handling.

Your practical work

Demonstrate both a successful request and an unavailable service using practice data.

Let's talk through it

What happens if the other service is unavailable?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An application you can build, run and improve
WEEK
20
Project 2: demonstrate your application

This week's goal

Review application behaviour, documentation and personal explanation.

Your practical work

Demonstrate Project 2's local version with tests and API instructions. Review initial portfolio material and potential role requirements.

Let's talk through it

Can you demonstrate your own contribution and answer follow-up questions?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An application you can build, run and improve
05

Weeks 21–24 / After building an application

AWS for Developers

Deploy an application on Amazon Web Services and understand the resources that keep it running.

Starting requirements, topics & tools

Before you startA working application, basic API knowledge and familiarity with the command line.

  • Understand cloud resources

    Connect the roles of computing, storage and networking to an application.

  • Configure access

    Use permissions and environment settings to control what the application can reach.

  • Deploy the application

    Move from a local program to an application running in a cloud environment.

  • Check how it runs

    Read logs, investigate failures and understand which resources contribute to cloud costs.

Tools & conceptsAWS / Terraform / Access controls / Application logs

WEEK
21
Understand your cloud environment

This week's goal

Understand command-line basics, compute, storage, networking, access and cloud costs.

Your practical work

Draw what Project 2 needs to run; identify which resources incur charges and how the lab is closed down.

Let's talk through it

Which resources cost money and how will you close down the lab?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An application you can build, run and improve
WEEK
22
Deploy on AWS and read the logs

This week's goal

Deploy the application and read logs.

Your practical work

Reach the practice application, inspect a request and diagnose a configuration error.

Let's talk through it

Which log entry helps you understand a failed request?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An application you can build, run and improve
WEEK
23
Repeat your setup with Terraform

This week's goal

Introduce Terraform as a way to describe and repeat the cloud setup.

Your practical work

Review a small infrastructure plan and explain its state and configuration in the controlled practice environment.

Let's talk through it

What will the infrastructure plan create, change or remove?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An application you can build, run and improve
WEEK
24
Project 2: your cloud milestone

This week's goal

Recreate, investigate and clean up the environment.

Your practical work

Demonstrate Project 2's cloud milestone and write a short runbook. Revisit gaps before moving on.

Let's talk through it

Can you recreate the environment and explain its configuration?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An application you can build, run and improve
06

Weeks 25–27 / After applications and APIs

System Design

Turn a requirement into a system design and explain why you chose that approach.

Starting requirements, topics & tools

Before you startExperience building a small application and familiarity with APIs and databases.

  • Define the real requirement

    Identify users, expected traffic, constraints and what the system needs to do.

  • Choose the components

    Describe the data, interfaces and responsibilities of each part.

  • Plan for growth and failure

    Reason about caching, queues, scaling and what happens when a component is unavailable.

  • Explain the trade-offs

    Compare alternatives in terms of complexity, reliability and cost.

Tools & conceptsArchitecture diagrams / Databases / Design notes

WEEK
25
Turn a requirement into a design

This week's goal

Translate a requirement into components, data and interfaces.

Your practical work

Draw Project 2, name the responsibilities and ask questions about unclear requirements.

Let's talk through it

Which requirement does each component serve?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An application you can build, run and improve
WEEK
26
Plan for growth and failure

This week's goal

Reason about growth, caching, queues and component failures.

Your practical work

Compare two design options using a modest example; explain why a simpler approach might be sufficient.

Let's talk through it

What happens when one dependency stops responding?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An application you can build, run and improve
WEEK
27
Explain your design decisions

This week's goal

Explain reliability, complexity and cost trade-offs.

Your practical work

Conduct a design walkthrough, answer follow-up questions and revise one decision.

Let's talk through it

What alternative did you consider, and why did you choose this design?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An application you can build, run and improve
07

Weeks 28–32 / After development and deployment

Production Engineering

Learn how a code change is reviewed, tested, released and monitored in a team workflow.

Starting requirements, topics & tools

Before you startYou can build an application and use Git. Basic deployment experience helps.

  • Work with a reviewable change

    Use branches, commits and pull requests to make a change understandable to another developer.

  • Make the environment repeatable

    Package an application with Docker and keep its configuration clear.

  • Automate the checks

    Run tests before a release and understand the steps in a delivery pipeline.

  • Investigate a release problem

    Use logs and metrics to find failures and plan how to recover from a bad change.

Tools & conceptsGitHub / Jira / Confluence / Docker / Delivery pipelines / Logs and metrics

WEEK
28
Package your application with Docker

This week's goal

Package the application with Docker and separate configuration.

Your practical work

Run Project 2 in a repeatable container and document what changes between environments.

Let's talk through it

What belongs in the image, and what belongs in configuration?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An application you can build, run and improve
WEEK
29
Automate your checks

This week's goal

Automate checks with a CI pipeline.

Your practical work

Use GitHub Actions for a teaching pipeline; deliberately fail a test and explain why the release stops.

Let's talk through it

What should stop a change from reaching the release stage?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An application you can build, run and improve
WEEK
30
Review, release and recover

This week's goal

Follow a reviewed release process with deployment and recovery steps.

Your practical work

Move one change through Jira, GitHub review and a controlled release; rehearse the recovery plan.

Let's talk through it

What will you do if the new release causes a problem?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An application you can build, run and improve
WEEK
31
Investigate a simulated incident

This week's goal

Investigate a simulated incident using logs and useful signals.

Your practical work

Reproduce a problem, record the cause and share a short explanation in the project's documentation.

Let's talk through it

Can you reproduce the problem and explain the cause clearly?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An application you can build, run and improve
WEEK
32
Your portfolio and application checkpoint

This week's goal

Consolidate the complete team workflow and prepare for relevant applications.

Your practical work

Demonstrate Project 2's complete delivery milestone. Review the CV and portfolio, practise a mock interview and create an application plan.

Let's talk through it

Does your portfolio demonstrate the skills a relevant role asks for?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An application you can build, run and improve
08

Weeks 33–38 / After Python and APIs

RAG Engineering

Build AI answers that use information from your documents. RAG means retrieval-augmented generation.

Starting requirements, topics & tools

Before you startComfort with Python and APIs, plus basic experience using a language model.

  • Prepare the documents

    Break source material into useful passages and retain the information needed to cite it.

  • Find relevant information

    Retrieve passages for a question and inspect whether the selected material is useful.

  • Generate an answer with sources

    Use the retrieved passages in a response and show where the information came from.

  • Evaluate the answers

    Test answer quality, unsupported questions and cases where the system should say it does not know.

Tools & conceptsPython / Language models / Document retrieval / Evaluation sets

WEEK
33
Understand language-model applications

This week's goal

Understand language-model APIs, instructions, output limits, cost and privacy basics.

Your practical work

Make a small model call and explain how you would check the answer; begin Project 3.

Let's talk through it

How would you check an answer that sounds convincing?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An AI assistant that shows its sources
WEEK
34
Prepare a document collection

This week's goal

Prepare documents, passages and metadata for retrieval.

Your practical work

Create a document-processing pipeline and show how a passage retains its source.

Let's talk through it

Can you trace a passage back to its source?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An AI assistant that shows its sources
WEEK
35
Find information with retrieval

This week's goal

Understand embeddings and retrieve relevant passages.

Your practical work

Compare retrieved results for a few questions and explain why a result is useful or irrelevant.

Let's talk through it

Why is one retrieved passage more relevant than another?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An AI assistant that shows its sources
WEEK
36
Answer with visible sources

This week's goal

Produce answers using retrieved information and visible sources.

Your practical work

Demonstrate an answer with citations and a question the documents cannot support.

Let's talk through it

What should happen if the documents cannot answer the question?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An AI assistant that shows its sources
WEEK
37
Evaluate answers and failure cases

This week's goal

Evaluate failure cases, permissions, latency and usage costs.

Your practical work

Create a small question set, identify failures and revise the system; discuss malicious instructions inside a document.

Let's talk through it

Which failed question would you improve first, and why?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An AI assistant that shows its sources
WEEK
38
Project 3: review your document assistant

This week's goal

Review, revise and demonstrate the complete document assistant.

Your practical work

Present Project 3, its checks and limitations. Practise explaining why a convincing answer can still be wrong.

Let's talk through it

Can you explain the retrieval, answer and evaluation steps?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An AI assistant that shows its sources
09

Weeks 39–44 / After an AI application

Agentic AI & MCP

Build AI workflows that use tools, keep track of their progress and ask for approval before an important action.

Starting requirements, topics & tools

Before you startStrong Python and API fundamentals, and experience building and checking an AI application.

  • Give an agent useful tools

    Define what a tool can do, what input it accepts and how its result is returned.

  • Control the workflow

    Track state, handle a failed step and set a clear point at which the agent should stop.

  • Connect tools with MCP

    Use the Model Context Protocol, a standard way to connect an AI application to tools and information.

  • Evaluate actions and add approval

    Inspect the steps taken, check the results and require a person to approve actions when appropriate.

Tools & conceptsPython / Tool APIs / MCP / Execution traces

WEEK
39
Define a useful agent workflow

This week's goal

Define a bounded workflow and structured tools.

Your practical work

Begin Project 4 with a small task and show when an ordinary program is enough.

Let's talk through it

Does this task need an agent, or would a simple program work?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An AI workflow with a person in control
WEEK
40
Track progress and recover from errors

This week's goal

Track state, retries, errors and stopping conditions.

Your practical work

Trace a workflow that fails part-way and demonstrate controlled recovery.

Let's talk through it

What happens after a failed step, and when should the workflow stop?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An AI workflow with a person in control
WEEK
41
Connect a tool with MCP

This week's goal

Connect a scoped tool through MCP, the Model Context Protocol.

Your practical work

Explain the request, allowed action and returned information in a small practice integration.

Let's talk through it

What can the tool access and what is outside its scope?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An AI workflow with a person in control
WEEK
42
Add approval and test boundaries

This week's goal

Require human approval for an action and test misuse cases.

Your practical work

Show an action awaiting approval, a rejected request and how the workflow handles each.

Let's talk through it

What happens when approval is refused or an instruction is misleading?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An AI workflow with a person in control
WEEK
43
Evaluate the complete workflow

This week's goal

Evaluate the workflow and prepare repeatable operation and documentation.

Your practical work

Test realistic cases, inspect traces and connect the project to the earlier review and release practice.

Let's talk through it

Which traces and checks show the workflow behaved as intended?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An AI workflow with a person in control
WEEK
44
Project 4: demonstrate and plan ahead

This week's goal

Consolidate the work, practise interviews and set the next learning plan.

Your practical work

Demonstrate Project 4, explain personal decisions, revisit applications and agree what to practise next.

Let's talk through it

What can you now demonstrate, and which skill will you practise next?

Use the feedback to revise your work. Revisit a smaller task if you need more practice before moving on.
An AI workflow with a person in control

YOUR PROJECT BRIEFS

Make something useful.
Know it well enough to explain it.

Follow the brief, check the result and handle a changed requirement. 20 educational briefs in this roadmap give each new skill a practical purpose.

PROJECT 01

A tool that collects and cleans data for you

Turn a messy operational export into a useful, checked summary. Then let the program collect its own input, so a job you did by hand runs on its own.

Weeks 5–16 · one tool, grown three times

What you create

  • Python program and sample files
  • Tests for missing and duplicate records
  • Collection step, run log and schedule
  • GitHub change history and setup notes
The next challenge

The input changes and a run fails. Add a new reporting rule and show that the earlier behaviour still works.

Practise explaining it

Walk through a record from source to result. Explain which checks make the number trustworthy, and what the program does when the source misbehaves.

PROJECT 02

An application you can build, run and improve

Build an API that accepts and tracks requests. Take the same application from your laptop to AWS, then through a reviewed release workflow.

Weeks 17–32 · one project, several delivery milestones

What you create

  • API, database and automated tests
  • AWS deployment and Terraform setup
  • GitHub review, delivery checks and a Jira task
  • Confluence handover and recovery notes
The next challenge

Handle an unavailable service, release a changed requirement and investigate a simulated failure.

Practise explaining it

Explain your design, demonstrate a change and show how you would recover from a release problem.

PROJECT 03

An AI assistant that shows its sources

Build a document question-answering assistant. Retrieve useful passages, show the sources and check what happens when the answer is missing.

Weeks 33–38

What you create

  • Document preparation and retrieval
  • Answers with source passages
  • Evaluation questions and failure notes
The next challenge

Remove a source or ask a question the documents cannot answer. Inspect and improve the response.

Practise explaining it

Describe how information was retrieved and why an answer needs checking, even when it sounds convincing.

PROJECT 04

An AI workflow with a person in control

Create a workflow that finds information and drafts an update. Require approval before it takes an action in another system.

Weeks 39–44

What you create

  • Tool definitions and an MCP connection
  • Workflow state and approval step
  • Execution traces and failure checks
The next challenge

Refuse approval, return a tool error and test an instruction that should not be followed.

Practise explaining it

Show what the agent can do, when it must stop and how you checked its actions.

WHEN YOU WANT MORE

Further projects,
once the foundations are yours.

Ordered from the most approachable to the most demanding. Take them on with guidance when the courses each one names are behind you.

StarterAfter Python Foundations

Tidy the folder you keep avoiding

Sort a downloads folder by type and date, rename files to a consistent pattern and write a log of everything that moved, so the change is reversible.

What you makeA script that sorts and renames, a log of every move and a dry-run mode that shows what would happen.

The question that tests it

Two files want the same name. Show what your program does instead of overwriting one of them.

StarterAfter Python Foundations

A report your spreadsheet builds for you

Read a CSV export, calculate the few numbers that matter and produce a formatted summary you could send to someone, without opening a spreadsheet at all.

What you makeA generator that reads the export, a formatted output file and a template you can change without touching the code.

The question that tests it

The export arrives with a missing column. Show whether your report fails loudly or produces a quietly wrong number.

StarterAfter Web Scraping & Automation

A watcher for a price you care about

Check a published price on a source you are permitted to use, keep the history and tell you when it moves beyond a threshold you set.

What you makeScheduled checks, a price history, a threshold alert and a record of every run including the ones that found nothing.

The question that tests it

The page changes and your selector stops matching. Show how you learn about that rather than assuming the price never moved.

StarterAfter Web Scraping & Automation

One digest instead of ten open tabs

Collect updates from a handful of permitted sources, drop the ones you have already seen and send yourself a single summary each morning.

What you makeMulti-source collection, a record of what you have seen, a scheduled summary and a delivery step.

The question that tests it

One source goes down. Show that the digest still arrives with the rest, and says what is missing.

StarterAfter Web Scraping & Automation

A tracker for the roles you want

Collect job postings from sources you are permitted to use, pull out the skills each one asks for, and compare them with the skills you can currently demonstrate.

What you makeScheduled collection, skill extraction, a gap list and a record of what changed week to week.

The question that tests it

A site changes its layout and a run collects nothing. Show how you noticed and what you fixed.

StarterAfter Web Scraping & Automation and Advanced Python

Market data, and why a backtest flatters you

Collect published price history, calculate a few indicators and test a simple rule. Then add costs, slippage and a different time period, and watch the result change. The lesson is measurement, not stock picking.

What you makeData collection, indicators, a backtest, and the same test repeated with costs and a different period.

The question that tests it

Explain why the first result looked better than the second. This is a teaching exercise in evaluation; it is not investment advice and recommends no strategy.

IntermediateAfter APIs & Integrations

A service that keeps what people send it

Accept a submission over an API, validate every field, store it and acknowledge it. Then handle the submission that arrives twice and the one designed to break you.

What you makeA validated endpoint, stored records, duplicate handling and tests for the inputs you did not expect.

The question that tests it

Someone submits the same form three times in a second. Show what you stored and why.

IntermediateAfter APIs & Integrations and Production Engineering

A scheduled pipeline that survives a bad day

Pull from an API on a schedule, process what arrives and store the result. Then make it behave when the source is slow, partly broken or returns yesterday's data.

What you makeScheduled runs, retries with backoff, a record of each run's outcome and a way to safely re-run a failed one.

The question that tests it

A run half-finishes. Show that re-running it does not double the data.

IntermediateAfter APIs & Integrations and Production Engineering

A bot that tells you when something breaks

A messaging bot that reports a daily summary and raises an alert when a check fails, so you find out before someone else does.

What you makeScheduled checks, a messaging integration, alert rules and a quiet mode that prevents repeat noise.

The question that tests it

Make a check fail repeatedly. Show that you are told once, not sixty times.

IntermediateAfter AWS for Developers

A watcher for your cloud spending

Read usage from your practice cloud account, show what each resource costs, and warn you before a forgotten instance turns into a bill.

What you makeUsage collection, a cost breakdown, a threshold alert and notes on shutting a lab down.

The question that tests it

Explain which resource drove the largest change, and what you would turn off first.

AdvancedAfter APIs & Integrations and RAG Engineering

A document triage service

Sort incoming documents into categories, attach a confidence level and send anything uncertain to a human queue rather than guessing.

What you makeClassification service, a confidence threshold, a review queue and a record of decisions.

The question that tests it

Feed it a document unlike anything it has seen. Show that it asks for review instead of choosing confidently.

AdvancedAfter APIs & Integrations and RAG Engineering

An assistant that answers from your database

Table-aware answering: the visitor asks a business question in plain words, the assistant writes the query, runs it and shows both the number and the query it used. Nothing is hidden.

What you makeQuestion-to-query step, a safe read-only connection, results shown with the query, and a set of test questions.

The question that tests it

Ask an ambiguous question. Show how the assistant asks for clarification instead of guessing a number.

AdvancedAfter RAG Engineering

A knowledge graph of your documents

Pull the people, products and events out of a document set and store how they connect. Then answer questions that need two or three facts joined together, which a single passage cannot answer.

What you makeExtraction pipeline, a graph of entities and relationships, and questions answered by following connections.

The question that tests it

Ask something the graph links wrongly. Show where the extraction went wrong and how you would catch it next time.

AdvancedAfter Agentic AI & MCP

A personal assistant for your working day

An assistant that reads a practice calendar and message export, drafts your day's summary and prepares replies. It waits for your approval before anything is sent.

What you makeScheduled summary, drafted replies, an approval step and a trace of every action considered.

The question that tests it

Refuse a draft and change an instruction. Show that nothing left the system without your approval.

AdvancedAfter Web Scraping & Automation, RAG Engineering and Agentic AI & MCP

A research assistant that gathers, reads and reports

The whole roadmap in one project. It collects material from permitted sources, indexes it so answers can cite a passage, then works through a research question and writes up what it found, with the gaps named and a person approving before anything is published.

What you makeScheduled collection, a retrievable index with sources, a multi-step research workflow, cited findings and an approval step.

The question that tests it

Ask it something the collected material cannot support. Show that it reports the gap instead of writing a confident paragraph anyway.

WHAT YOU HAVE, AND WHEN

You don't wait until week 44
to have something to show.

This is the complete road. Your work becomes worth showing long before the end of it, and the plan marks exactly where.

  1. Week 8

    A program that does a real job

    A tool that turns a messy file into a checked result, with tests and a change history.

  2. Week 16

    A task you used to do by hand, running by itself

    The same tool collects its own data, validates it and runs on a schedule.

  3. Week 20

    An application, and your first career checkpoint

    An API with stored data and tests. Enough to discuss your work with a relevant role in mind.

  4. Week 32

    Deployed, tested, reviewed — start applying

    A system running on AWS, released through a reviewed workflow, with a failure you investigated and can explain.

  5. Week 44

    AI you can evaluate and control

    Document-grounded answers with sources, and a supervised agent that stops for approval.

Where you start and how quickly you move depends on your experience and the time you can give it. Start applying when your work demonstrates what a role asks for, not when a week number says so.

YOUR WORK. YOUR NEXT OPPORTUNITY.

Prepare for the role.
Keep growing in it.

Build skills, put your work into words and prepare for opportunities. When you join a team, keep learning with people you can talk to.

  1. 01

    Build your evidence

    Bring together projects you understand. Write a clear CV and profile that reflect your actual experience.

  2. 02

    Practise the conversation

    Walk through your projects, answer follow-up questions and use mock interviews to find what needs practice.

  3. 03

    Start applying when ready

    Choose roles that match the skills you can demonstrate. Discuss application feedback and keep improving.

  4. 04

    Keep learning after you join

    Get educational guidance on unfamiliar work, asking useful questions and communicating your decisions.

STAY CONNECTED

Your learning can continue
beyond the course.

Bring a question. Share a useful approach. Work through an idea together. Our community is built around helping each other keep learning as our responsibilities grow.

Discuss and practiseWork through concepts, project decisions and interview questions together.

Learn from the next challengeTalk about general technical approaches using practice examples when discussing workplace questions.

Know what support includesTalk with us about the structured support period, group activities and ongoing community access before joining.

BEFORE YOU BEGIN

A few things
to talk through.

I've never coded. Can I choose the Python roadmap?

Yes. Python Foundations begins with your first program, files and small practical tasks. The analytics roadmap also begins with foundations, using Excel. Choose the kind of work that interests you: building applications, or investigating and explaining data. You do not need coding experience for the first course in either.

Do I need to take every course in a roadmap?

The sequence helps when you are building from the beginning. If you already have experience, read the starting requirements and talk with us about a practical starting point. Later courses build on the earlier skills; a familiar title alone is not a reason to skip the foundation.

Are the week numbers a fixed completion deadline?

This is a suggested weekly learning sequence. Your starting point and practice may change the pace. Talk with us about the teaching schedule, time commitment and support before joining.

What are RAG and Agentic AI?

RAG helps an AI application answer using information retrieved from documents, with sources you can inspect. Agentic AI adds tools and a controlled workflow, such as finding information and drafting an update for a person to approve. MCP is the Model Context Protocol, a way to connect AI applications to tools and information. Python and API skills come first.

Will I be able to ask questions and discuss my work?

Learn through teaching calls, practical tasks and review conversations. Bring your attempt and questions, discuss the feedback, then revise and explain your work. If a concept needs more practice, work through a smaller task before building on it.

What does it cost, and why is there no price on the site?

Send us an enquiry first. We will talk through where you are starting, what you want to reach and which roadmap fits, and then discuss the price for the part you actually need. There is no checkout here on purpose: what suits someone starting from nothing is different from what suits someone already working in QA, and quoting one number to both would serve neither. Ask about the teaching schedule, the support included and any software, cloud or AI usage costs in the same conversation.

YOUR NEXT STEP

Tell us where you are.
Let's find your next step.

Share what you have been doing and what you would like to change. There is no checkout on this site on purpose: we would rather understand where you are before talking about money.

  1. 01Tell us where you are and what you want to reach.
  2. 02We get in touch and talk it through properly.
  3. 03Together we work out which roadmap fits, and where you should start.
  4. 04Then we discuss the price for the part you actually need.

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