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Articles by Venkataraghulan (8)
AI-First Screening: What Your Students Now Have to Show
At most large IT recruiters, AI screens resumes before any human reads them. Here is what the algorithm scores, what passes the filter, and how to prepare students.
Outcome-Based Education & Employability: Aligning NEP 2020 with Placements
Outcome-based education and employability are the same goal described twice: define the graduate you want, then design and measure backward. How to align the two.
AI Skills for Engineering Students: What to Teach, and When
The useful question about teaching AI is not only what, but when. A year-by-year sequence that puts fundamentals first and treats judgment as the real AI skill.
Coding Readiness: Helping More Students Write Production-Ready Code
Production-ready code is correct, readable, tested, and maintainable, not just code that runs once. How to help more students, not only the toppers, reach that bar.
Mapping AI & Data Skills into a 4-Year Engineering Curriculum
The hard part of adding AI and data to a degree is fitting it into four already-full years. How to map it into the existing structure using NEP 2020, not bolt it on.
The Skills Recruiters Expect from Freshers in 2026: A Checklist
A practical checklist of what recruiters actually screen freshers for in 2026, grouped into a durable core and a current technical layer, with the realistic bar for each.
AI and Fresher Hiring: What the Shift Means for Your Placement Cell
AI is not removing entry-level engineering roles. It is raising the floor of what they assume. Here is what that asks of a college placement cell, in practical terms.
Skill-Gap Analysis for Colleges: Spot Readiness Gaps Before Drives
A baseline skill-gap analysis, including AI fluency, shows a college exactly where its students stand, so it can act before drives instead of after rejections.