Project, not magic
One dataset, one model, a clear write-up.
Campus workshop
ML starter project
A first supervised model students can defend without pretending they shipped a production ML platform.
What students will learn
Outcomes for this campus batch
- Train/test split in practice
- A simple model and its metric
- Overfit in language a student can say out loud
- Where ML shows up in real software (and where it does not)
2Campus days
16Hours
1Model
LiveMentors
Highlights
Built for college labs, not an online store
Campus
Your labs; we bring the notebook trail.
Live
Mentors stop cargo-cult sklearn.
Interview close
Explain the metric to a non-ML engineer.
Labs & projects
What the batch will build
Students work in your labs. These are the artefacts they leave with.
Baseline model
Something simple before anything fancy.
One improvement
A feature or a different model they can justify.
Limitation note
What the model must not be used for.
How you can host it
Choose a campus format
No individual checkout. The college books the batch and we deliver on site.
2-day starter
2 days
- Data
- Model
- Explain
Curriculum
How the campus days are structured
- 01
Problem framing
Label · Leakage talk · Split
- 02
Fit a model
Baseline · Metric · Sanity checks
- 03
Explain
Who it helps · Who it fails · Demo
Mentors
Know the engineers who run the lab
Practising Shribi engineers — not a rented recording of someone else's course.
Hemant Sharma
Software Engineer, Shribi Technologies
Builds production software at Shribi and runs campus labs so students practise the same problem-solving we use on client work.
Gaurav Singh
Sr. Software Engineer, Shribi Technologies
Architects applications and coaches student batches on structure, debugging, and how interviews actually run.
Krishna
Sr. Software Engineer, Shribi Technologies
Focuses on system design and backend thinking — useful when DSA has to connect to real APIs and products.
Still planning the batch?
Get a call back for your college
Tell us the campus, student year, lab size, and preferred dates. We will propose a schedule for ML starter project.
FAQ
Questions colleges ask before they book
Is this an online course we buy individually?
No. This is an on-campus workshop that Shribi runs at your college. Placement cells, HODs, or clubs book a batch. Students do not purchase a seat online.
Where is the training held?
In your campus computer labs. We travel to colleges; we started with the GLA University ecosystem in Mathura and run programmes for other engineering campuses on request.
Do students get a certificate after the ML starter project?
Yes. Participants who complete the labs receive a Shribi workshop completion note. It is not a substitute for a degree — it records the project and problem work they did on campus.
What should the college provide?
A lab with machines, a projector or screen, and a student list. We bring the curriculum, problem sheets, mentors, and the closing demo format.
Can this connect to internships or hiring?
If the college opts in, strong participants can be reviewed privately through Shribi Talent. We do not publish a public directory of students.