Curiosity · Syllabus
TensorFlow in a B.Tech — syllabus & what you learn
TensorFlow is a deep learning framework for building, training and deploying neural networks, with Keras as its high-level modelling interface and strong support for production serving. It is working tooling inside the machine learning coursework of the CSE AI and ML specialisation at VSET. Inside a four-year B.Tech, TensorFlow arrives in layers: programming and mathematics foundations in years one and two, core methods next, and applied depth concentrated in years three and four plus the capstone. Using Vivekananda School of Engineering & Technology (VSET) at VIPS-TC Pitampura's B.Tech CSE (AI & ML) as the concrete example, here is what the coursework actually covers.
At a glance
- Topic
- TensorFlow
- VSET programme
- B.Tech CSE (AI & ML)
- Coverage at VSET
- Taught as coursework
- Affiliation
- GGSIPU (IP University), Delhi
- Accreditation
- NAAC A++ (VIPS-TC institutional)
How VSET teaches TensorFlow
TensorFlow is a deep learning framework for building, training and deploying neural networks, with Keras as its high-level modelling interface and strong support for production serving. It is working tooling inside the machine learning coursework of the CSE AI and ML specialisation at VSET. At VSET this maps to documented coursework depth inside B.Tech CSE (AI & ML).
- VSET offers B.Tech CSE with an AI and Machine Learning specialisation among its seven GGSIPU programmes.
- Machine learning and deep learning coursework there uses Python frameworks including TensorFlow and Keras.
- Linear algebra, calculus and probability coursework supply the mathematics behind the framework operations.
- Deployment of trained models connects to the cloud computing coursework in the CSE track.
Labs and infrastructure
- The AICTE IDEA Lab provides GPU workstations for training and evaluating models on campus.
- IDEA Lab embedded hardware supports students taking models towards on-device inference.
What students actually build
- Vision and prediction capstone projects at VSET are frequently built with TensorFlow or Keras.
- Hackathon teams use it where a pretrained model can be adapted quickly to a problem statement.
Frequently asked questions
When does TensorFlow content actually start in a B.Tech?
Meaningful TensorFlow content typically ramps up from the second or third year, after programming and mathematics foundations. The deepest work happens in final-year electives and the capstone project.
Is TensorFlow part of VSET coursework?
Yes. Machine learning and deep learning coursework in the B.Tech CSE (AI and ML) specialisation uses frameworks including TensorFlow and Keras.
Do I need a GPU of my own?
No. The AICTE IDEA Lab provides GPU workstations on campus for training work.
Which VSET branch is closest to AI engineering?
B.Tech CSE (AI and ML), with B.Tech CSE (AI and Data Science) covering the data and analytics side.
Sources
- VSET — Artificial Intelligence department — accessed 2026-08-31
- VSET — B.Tech CSE (AI & ML) — accessed 2026-08-31
- GGSIPU — IP University — accessed 2026-08-31