The program is built around the student's academic stage, so technical development starts early and intensifies as placements get closer — grounded in real project experience from initiatives including TiH IoT Chanakya, C-DOT and SAM 2.0.
| Academic Stage | Primary Focus | Key Outcomes |
|---|---|---|
| 2nd Year | Foundations & early industry exposure | DSA, competitive coding, Agentic AI, certification, open source |
| 3rd Year | Advanced skills & internship readiness | DevOps, modern web, advanced coding, projects, internships |
| Final Year | Placement-focused acceleration | Crash course, coding assessments, CS fundamentals, mock interviews, placement readiness |
Students receive early structured exposure to programming and problem-solving so they have sufficient time to build depth before the internship and placement cycle.
Complexity analysis, recursion, trees, graphs, hashing, dynamic programming.
Timed coding practice, contests and competitive programming strategy.
Generative AI, AI-assisted development, agents, tools and workflow orchestration.
Professional Git/GitHub workflows — issues, branches, pull requests, reviews.
Training shifts to advanced technical skills, modern engineering practices and hands-on project work in preparation for internships.
Linux & shell, Git/GitHub, Docker, Kubernetes fundamentals, CI/CD, cloud basics, monitoring & deployment.
Advanced DSA, dynamic programming, graphs and optimization aligned to internship screening patterns.
Frontend & backend development, APIs, databases, authentication, testing and deployment.
Tool-using agents, multi-step workflows and AI-assisted development applied to real projects.
Problem identification, architecture, technology selection, implementation, Git/GitHub practices, testing, deployment, documentation and final presentation — aimed at demonstrating genuine engineering capability.
A focused, intensive crash course for final-year students with one objective: maximize placement readiness within a defined period, customizable around the institution's placement calendar and target companies.
Competitive coding and company-style coding tests.
OOP, DBMS, Operating Systems and Computer Networks.
Interview preparation, mock interviews and placement simulations.
Project-based technical discussions and software engineering expectations.
Emphasis is on intensive practice, assessment readiness and interview performance — not purely theoretical instruction.
So we built both directly into the program.
Technical preparation covering:
Potential areas: software development, AI/ML, web development, DevOps/cloud, and research-oriented internships.
For eligible, high-performing students, we connect through our professional network:
Referrals improve access to opportunities — they are not a guarantee of selection, internship or employment.
Programs on Generative AI, Agentic AI, DevOps, cloud and modern engineering practices.
As a complementary add-on, we support faculty with journal and research writing — from problem identification and literature review through to manuscript refinement and submission prep.
Research contribution and authorship stay entirely with the faculty and institution — we provide guidance, not ghostwriting.
Team-based, real-world problem statements with mentorship from industry professionals.
A chance to spot standout talent for further internship and referral opportunities — while giving students a high-energy, applied learning experience.
Every academic module — 2nd Year, 3rd Year and Final Year — is priced at a flat ₹1,999 per semester, per student.
