Learn
Train and evaluate ML models.
Prepare data, choose an algorithm, and measure a model honestly on held-out data.
University Programmes · University · 4–6 semesters
AI & Machine Learning. Machine learning, inside your degree.
Rooman's AI & Machine Learning track is the flagship track of the Credit-Based Integrated AI Course, which universities embed in B.E., B.Tech., B.Sc. and BCA degrees with formal credits. It runs over 4–6 semesters, taught by Rooman trainers alongside your college faculty and scheduled around your academic calendar, and covers machine learning, deep learning, NLP, computer vision and agentic AI.
180 hours7 modulesCredit-basedCapstone project
What you'll be able to do
Build models that work on real data.
This is the flagship track for engineering students. It sits inside your degree timetable and counts toward it, with credits as set by your university.
Apply
Work with text and images.
Build deep learning models for language and vision tasks with standard frameworks.
Build
Ship an agentic AI project.
Combine models, tools and data into an application you can demonstrate.
Skills covered
- Python for machine learning
- Supervised and unsupervised learning
- Model evaluation and validation
- Neural networks and deep learning
- Natural language processing
- Computer vision
- Agentic AI and tool use
- Project delivery in a team
Who it's for
Built for engineering students.
The track is for undergraduates at colleges that partner with Rooman. You enrol through your college, not directly with Rooman: the course runs where your university has a partnership with Rooman.
Roles where these skills are used
- Machine Learning Engineer (entry level)
- AI Engineer (graduate)
- Data Scientist (associate)
- Computer Vision Engineer (entry level)
- NLP Engineer (entry level)
- AI Application Developer
Entry requirements.
- Enrolled in a B.E., B.Tech., B.Sc. or BCA programme at a partner college
- Chosen as an elective or integrated track, as your university's scheme allows
- Basic programming from your first year; no AI experience needed
Not sure which course fits? Take the 10-minute career assessment, or talk to a counsellor.
180 hours · 7 modules
A curriculum paced by semester.
Seven modules, from Python and mathematics to agentic AI, with a project semester at the end. The order fits your academic calendar.
01Python and mathematics for AI24 hrs
The programming, linear algebra and probability that machine learning rests on.
Topics covered
- Python, NumPy and pandas
- Linear algebra for ML
- Probability and statistics
You produce: working notebooks for data and maths exercises.
02Machine learning foundations24 hrs
Regression, classification and clustering, with honest evaluation.
Topics covered
- Regression and classification
- Clustering and dimensionality reduction
- Train, validation and test splits
- Metrics and model selection
You produce: a trained and evaluated ML model.
03Deep learning26 hrs
Neural networks and how to train them well.
Topics covered
- Neural network basics
- Training, loss and optimisation
- Convolutional and recurrent networks
- Overfitting and regularisation
You produce: a neural network trained with a standard framework.
04Natural language processing26 hrs
Turning text into features and models.
Topics covered
- Text preprocessing and embeddings
- Sequence models and transformers
- Text classification and extraction
You produce: a text classification model.
05Computer vision26 hrs
Image models for classification and detection.
Topics covered
- Image data and augmentation
- CNNs for classification
- Object detection basics
- Transfer learning
You produce: an image classifier.
06Agentic AI24 hrs
Systems where models plan, call tools and act on data.
Topics covered
- Large language models in applications
- Tool calling and planning
- Agent evaluation and safety
You produce: a working AI agent.
07Capstone project semester30 hrs
A team project that brings the track together.
Topics covered
- Problem framing with a faculty guide
- Data collection and modelling
- Deployment of a demo
- Final report and viva
You produce: a demonstrated AI project and report.
Tools covered
The tools you'll work with.
You work in the Python tools that industry teams use, in your college's labs.
| Tool group | Tools | What you use them for |
|---|---|---|
| Language | Python, Jupyter | Write and run every exercise |
| Data | NumPy, pandas, Matplotlib | Prepare and explore data |
| Machine learning | scikit-learn | Train and evaluate classical models |
| Deep learning | PyTorch or TensorFlow | Build neural networks for text and images |
Capstone
Build an AI project. Then present it.
In the final semester your team takes a real problem from framing to a working demo, guided by Rooman trainers and your faculty, and presents it for assessment.
Every module ends with a hands-on lab in your college.
What you finish with.
- A trained and evaluated ML model
- A deep learning model for text
- An image classifier
- A working AI agent
- A capstone project with report
Your credential
Credits toward your degree.
Credits toward your degree. The track counts toward your degree, with credits as set by your university.
Assessment follows your university's scheme, with Rooman trainers and your faculty assessing the work together.
What's included
Everything you need to finish.
- Taught by Rooman trainers alongside your faculty
- Scheduled to fit your academic calendar
- Labs every semester and a capstone project
- Credits counted toward your degree, as your university sets them
- A curriculum aligned with your university's academic council
- Placement and hackathon support through your college
Before you enrol
Questions engineering students ask.
Can't find your answer? Call 080 6945 1000 or WhatsApp us.
Does it count toward my degree?
Yes. It is a credit-based track, with credits as set by your university.
Is my college a partner?
Ask your department or placement office, or a Rooman counsellor. You enrol through your college, not directly with Rooman: the course runs where your university has a partnership with Rooman.
Can my university partner with Rooman?
Yes. Universities embed the course in their degrees, and a custom track can be co-created with the academic council.
Who teaches it?
Rooman trainers, alongside your college faculty.
How long does it take?
4–6 semesters, scheduled to fit your academic calendar.
Do I need AI experience?
No. Basic programming from your first year is enough to begin.
Which degrees can include it?
B.E., B.Tech., B.Sc. and BCA programmes at partner colleges.
What else does Rooman run with colleges?
Honours programmes, which are extended tracks run with universities, and SkillHub short industry certification programmes.
How do I find out fees and batch dates?
Talk to a Rooman counsellor on 080 6945 1000 or WhatsApp +91 97390 86029. They will share current fees, payment options and upcoming batch dates.
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180 hrsCredit-basedCloud & DevOpsBuild, ship and run software in the cloud.For universitiesBringing this to your university?Embed this track in your degree programmes with formal credits, taught with your faculty.Talk to usNext step
Start with a conversation.
Tell us your college, course and year, or your university, and a counsellor will explain how the tracks work.
- Call: 080 6945 1000
- WhatsApp: +91 97390 86029
- Email: hello@rooman.com
Course details reviewed on 25 September 2026.