Built for the jobs, not the hype
Most AI courses stop at prompts and a demo. Employers hire people who can build, test, secure, deploy and explain an AI system, and who understand the data under it.
Learn the patterns, not one product
Every lab runs through a provider layer. Use free open models on your laptop, then swap in OpenAI, Anthropic, Google or Mistral with one setting.
A track for your job
Admin, developer, tester, DevOps, release, data, security, BA or architect: twelve role tracks turn the shared core into the job you want.
Tested, secured, shipped
A third of the core covers evaluation, security, privacy, Docker, CI/CD, cloud, monitoring and release, the work most courses skip.
Analytics built in
SQL, statistics, pandas and dashboards are a full pillar, so you can measure what your AI does and move into analyst roles too.
Six pillars, every session mapped
Open any session for its topics and hands-on lab. Switch batch to see exactly when it runs. The capstone follows your 12-session role track.
12 role tracks
Twelve live sessions each, with a portfolio project and an optional certification target. Take one after the core, or on its own if you already work in IT. Tap a track to open it.
Find your route
A short skills diagnostic places you. Experience helps you move faster, and you can test out of sessions you already know.
One company, built end to end
Every lab works on the same fictional business, so you finish with a complete system and a story to tell in interviews.
Orbitel Broadband
A UK broadband and mobile provider with 400,000 customers. It runs a contact centre, a field-engineer network and a help centre with hundreds of policy articles, and it is losing customers it can't explain. Rich enough to need analytics, RAG, agents, testing, security and operations.
400K CUSTOMERS·CONTACT CENTRE·FIELD ENGINEERS·HELP CENTRE·NETWORK OPS
Free-first, industry-standard tools
You can complete every core lab without paying for a model or cloud service. Paid APIs and enterprise platforms are shown as swap-ins, so you recognise them at work.
Session notes
Diagrams, key terms and the interview angle for every session.
Lab sheet + starter code
Step-by-step build with a stretch task and a reference solution.
Recordings
Every class recorded for catch-up from any time zone.
Quiz + misconceptions
A short check and the mistakes people commonly make.
Code and work review
Pull-request reviews on your labs and projects.
Interview bank
Python, SQL, RAG, agent, testing and security questions.
Placement assistance
CV and LinkedIn rebuild, mock interviews and referrals where we can.
Quarterly refresh
Labs updated as models, SDKs and cloud services change.
Same programme, two schedules
Times are confirmed after registration, set for UK evenings and weekends, with recordings for other time zones.
Weekday batch
- Core (150)
- 30 weeks
- Role track (12)
- About 2½ weeks
- Capstone (10)
- 2 weeks
- Full route
- About 35 weeks
- Suits
- Graduates, career changers, steady daily practice
Weekend batch
- Core (150)
- 25 weekends
- Role track (12)
- 2 weekends
- Capstone (10)
- About 2 weekends
- Full route
- About 29 weekends
- Suits
- People in full-time work
Full route
From zero to a job-ready portfolio. Recommended for most people.
Fast-track
For people with 2–4 years in IT who pass the diagnostic.
Specialist
For working professionals adding AI to the role they already have.
Optional certification targets
The programme is vendor neutral. These exams line up with what you learn, if you want a badge from a cloud or data vendor. Exam fees are paid to the vendor, and exam names change, so we confirm the current version before you book.
Founder · Lead instructor
Anil Malneni
Around 20 years in enterprise technology across administration, development and architecture, delivering in India, the USA and the UK, and now a senior technical architect at a global financial institution, where he uses AI on real enterprise projects every day. He has trained IT professionals for more than 15 years. Every class ends with how the technique is used on a real project.
Before you enquire
I have no IT background. Can I join?
Yes. There are no prerequisites. The Launchpad starts with how software, the cloud and AI work, and Code Foundations teaches programming from the first line. You need basic computer skills and around four to six hours a week for labs.
I already work in IT. Do I have to start from the beginning?
No. A skills diagnostic places you, and you can test out of sessions you already know. Many working professionals take selected pillars plus a role track, or a role track on its own.
Is this tied to one AI company?
No. You learn patterns that work with any provider. Labs run on free open models and free API tiers through a provider layer, and we show OpenAI, Anthropic, Google and Mistral as swap-ins, plus one primary cloud on a free tier with the others compared.
Do I need to pay for AI services or the cloud?
No. Every core lab can be completed with free tools and free tiers. We teach budget alerts before you touch any paid service. Some role tracks optionally show paid enterprise platforms.
What computer do I need?
A laptop with at least 8 GB of memory (16 GB is better for running local models), a modern browser and reliable internet. Windows, macOS or Linux all work. We install everything together in the Launchpad.
Which batch should I choose?
Weekday suits people who can give an hour each evening. Weekend suits people in full-time work. Content, labs and projects are identical.
Does it cover superintelligence and the future of AI?
Yes, in plain terms. The Launchpad covers the path from rules to agents, what AGI and superintelligence mean, and what is real today versus debate. Responsible AI and governance run through the whole programme.
Will this get me a job?
No one honest can promise a job. You leave with a portfolio of working, tested projects on GitHub, a role-specific capstone, a rebuilt CV and LinkedIn, mock interview practice and our placement assistance, including referrals where we can make them.