Artificial Intelligence · Laxmi Nagar
Machine learning foundations first, then generative AI and retrieval — finishing with an application you have built, evaluated and can defend under questioning rather than a certificate saying you attended.
The thing that separates people who can use AI from people who can build with it is evaluation.
Anyone can change a prompt and feel that the output improved. Almost nobody builds a set of test cases first, measures against it, and can then say whether a change actually helped or just felt better on the three examples they happened to look at.
That habit is the spine of this course, and it is the question a serious interviewer asks.
It is tempting to start with the exciting part, and courses that do produce students who are fluent for about a year.
Machine learning foundations come first here — how a model learns, what overfitting looks like, why a baseline matters — because generative systems sit on top of that and behave incomprehensibly without it. Retrieval, embeddings and evaluation all make sense once the underlying ideas are in place, and are magic otherwise.
Class 12 mathematics is enough, and the first module teaches what is needed geometrically rather than as proofs.
Gradients as which way is downhill. Vectors as directions with length. Probability as how surprised you should be. That framing is sufficient for everything in the course, and students from commerce and other non-engineering streams complete it regularly.
If you are worried about this specifically, come and sit in on the first module before deciding.
Most NCR AI roles are in Gurgaon, Noida and central Delhi rather than East Delhi. Expect a commute or a move, and treat any promise otherwise with suspicion.
There is a second route people underuse: applying this inside a job you already have. Automating a reporting process, building a retrieval assistant over your company’s own documents, or replacing a manual review step is frequently a faster path to being paid for AI work than competing for a titled role as a fresher.
S-551, School Block, Nehru Enclave, Shakarpur — walking distance from Laxmi Nagar metro station. Machines are provided; a laptop helps for practice between sessions but is not required to start.
Full syllabus, module list, projects and fees are on the course page. Nothing about it changes by locality — the batches run at Shakarpur.
Python, machine learning foundations and applied generative AI in one track — ending with a retrieval-augmented application you have built, evaluated and can explain end to end.
Questions
You need Class 12 mathematics and willingness to work through the first module. Linear algebra, gradients and probability are taught geometrically — as which way is downhill rather than as proofs — which is enough for everything that follows. Students from commerce streams complete this regularly.
No, and that distinction matters. Prompting is one module. The rest is machine learning foundations, evaluation, and building retrieval systems that work on your own data. Courses that are only prompting date within a year; the underlying material does not.
Realistically most NCR AI work is in Gurgaon, Noida and central Delhi, so expect a commute or a relocation. The other honest route is applying AI inside a non-AI job — automating work at a company you already work for is often a faster path than competing for a titled AI role as a fresher.
Four projects including a working retrieval-augmented assistant over documents you choose, with an evaluation set you built to measure whether changes made it better. Being able to say what you measured and why is what separates this from a course you watched.
Next step
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