Academics

Six programs. One intensive year of practical learning.

Every program runs for 12 months: weekly practical classes, an interview-style assignment and a minor project each week, a major project and test at every month-end — and internship applications open from month 7. Choose a software-engineered or hardware-engineered track.

How the year runs

The weekly and monthly rhythm

The same practical cadence applies to all six programs, so you always know what the week ahead looks like.

Every week

A live instructor-led online class paired with a hands-on practical on that week's topic.

Weekly mock test

A mock test / interview-style assignment based on that week's topic, reviewed by faculty.

Weekly minor project

A small shippable project that applies the week's topic in practice.

Every month-end

A major test covering the full month plus a major project submission.

Top scorer reward

The top scorer in each month-end major test gets the following month's fee waived completely.

From month 8

You become eligible to apply for internships, and our placements team starts pushing you for remote part-time roles.

Programs

Choose your track

All six programs are divided into two schools of engineering — pick the one that matches how you like to build.

01

Software Engineered Programs

Fully online one-year tracks in AI, data, security and cloud engineering — every concept practised in cloud-based labs through weekly builds and month-end projects.

02

Hardware Engineered Programs

Online one-year tracks in chip design and embedded computing, run entirely through industry simulation tools, virtual labs and remote-access hardware boards.

AI/ML

AI & Machine Learning

One year of building AI systems end-to-end — from hands-on model training to production LLM pipelines, evaluation and responsible deployment.

Month-by-month curriculum

Months 1–2
  • Python for AI lab
  • Math for ML, applied
  • Data wrangling practicum
  • Weekly interview assignments
  • Minor project: data pipeline
  • Month-end major project + test
Months 3–4
  • Classical machine learning
  • Feature engineering lab
  • Model evaluation & metrics
  • Weekly interview assignments
  • Minor project: predictive model
  • Month-end major project + test
Months 5–6
  • Deep learning with PyTorch
  • Computer vision lab
  • NLP fundamentals
  • Weekly interview assignments
  • Minor project: trained network
  • Month-end major project + test
Months 7–8
  • LLM engineering & RAG
  • MLOps and model serving
  • Internship applications open (from month 8)
  • Weekly interview assignments
  • Minor project: AI application
  • Month-end major project + test
Months 9–10
  • Fine-tuning & evaluation harnesses
  • Responsible AI practicum
  • Mock technical interviews
  • Weekly interview assignments
  • Minor project: evaluated LLM app
  • Month-end major project + test
Months 11–12
  • Capstone AI product
  • Research paper implementation
  • Portfolio & resume studio
  • Final major project
  • Capstone defence
  • Placement readiness certification

Curriculum shown here is an AI-drafted, industry-oriented outline pending institutional review and accreditation. It is not presented as an accredited syllabus.