Track 1
Student marks analyser
A command-line tool that reads a class marks file, calculates averages and highlights students who need support. Teaches file handling, dictionaries and clean function design.
Outcomes
What students and colleges walk away with
Defined skills, a project a student can defend, and records the institution can actually file. Stated plainly, with the limits included.
For students
- Practical Python and AI tool skills matched to the track they joined
- At least one project they can open, run and explain without help
- A GitHub or portfolio record where the track includes it
- Practice explaining their work in a short viva-style review
- Enough vocabulary to discuss AI credibly in interviews and project reviews
- A completion certificate naming the track and hours actually completed
For the college
- Attendance records and a weekly completion summary
- A project completion overview suitable for internal and accreditation records
- A programme structure that can be repeated next semester with minimal planning
- A named point of contact throughout the cohort
- Honest reporting, including where results fell short
What students actually build
Representative projects for each track. Exact briefs are adapted to the branch and to what the cohort is capable of finishing well.
Track 2
Automated study-notes summariser
A script that takes lecture notes or a PDF and returns a structured summary and question set using an LLM API. Students learn prompt design and how to handle API responses safely.
Track 3
Department FAQ assistant
A deployed web application that answers questions from a college's own documents using retrieval. Students ship it, share a link and explain every part of the pipeline.
Track 4
Multi-agent research assistant
A system where separate agents plan, search, draft and review, coordinating through tool calls and shared memory. Students handle failure cases, not just the happy path.
Track 5
Workflow automation for a real task
An automation for something the student actually does weekly — attendance collation, report formatting or content drafting — built with no-code AI tools.
Track 6
Portfolio of four projects
Students complete the progression end to end, finishing with a GitHub profile that shows range: fundamentals, tooling, a deployed app and an agentic system.
How progress is assessed
Assessment is designed to show whether a student can do the thing, not whether they attended.
Weekly practice completion
Each week's practice set is checked for completion. This is the earliest signal that a student is falling behind, and it is where we intervene.
Every weekProject increments
The final project is built in stages across the track, so progress is visible throughout rather than only at the end.
OngoingViva-style review
Students walk through their own project and answer questions about the choices they made. Copied work becomes obvious immediately.
Final fortnightCompletion report
The college receives attendance, practice completion and project status per student — reported accurately, including students who did not finish.
End of cohort
Student path at a glance
Most colleges run stages one and two in the first semester and stages three and four in the second.
Basics
Python fundamentals, or no-code tools for non-CSE branches
AI tools
Prompting, APIs, workflows and simple automation
Build
A first AI application, deployed and explained
Advance
Optional agentic systems for students ready to go deeper
The limits, stated plainly
A programme is only useful to a college if the claims around it are accurate.
- We do not guarantee placements or job offers.
- Outcomes depend on student attendance, effort and prior readiness.
- We do not claim that every student will become an AI expert in a few weeks.
- We focus on practical skills and projects that students can actually show.
Students who attend under roughly two thirds of sessions rarely complete a project, whatever the track. We flag this early rather than at the end, so the department can act while it still helps.
Next step
Ready to plan a cohort?
Tell us your student numbers, branches and preferred months. We will send a written proposal with dates, pricing and deliverables — usually within two working days.