A structured 12-month roadmap for CAT preparation covering Quant, VARC, LRDI, mock tests, revision, and interview readiness.
A focused 90-day CAT preparation strategy for late starters and repeat candidates.
A clear breakdown of the CAT exam pattern — sections, question types, marking scheme, and duration — for first-time and repeat test takers.
A realistic CAT preparation approach for working professionals balancing a full-time job with exam preparation — time management, pacing, and what to prioritize.
An introduction to the Common Admission Test (CAT), India's most important MBA entrance exam.
Why CAT results are reported as a percentile rather than a raw score, how normalization works across exam slots, and what percentile range different IIMs typically expect.
A topic-by-topic breakdown of the CAT syllabus across VARC, DILR, and Quantitative Aptitude, with guidance on where to focus first.
A realistic, non-overwhelming plan for coding interviews — what they actually test, how to practise so it transfers, and why explaining your thinking out loud matters as much as the answer.
A sane starting point for DSA that avoids the two common traps — grinding problems with no understanding, and drowning in theory with no practice — plus the order to learn topics in.
A structured, practical course in Git and GitHub, taught through the actual workflow used to build and maintain a production Node.js site — not a shallow command dump.
What actually happens between typing a hostname and getting an IP address back — the lookup chain, caching layers, and why DNS is so often the first suspect in an outage.
The single most valuable skill in a fast-moving field: teaching yourself a new tool or language without a course. A repeatable method that beats aimless tutorial-hopping.
The HTTP status codes that actually show up in day-to-day support and operations work, what each one really means, and which ones point at the client vs. the server.
An overview of IIM Lucknow, its programs, admissions, and career outcomes.
What an IIS application pool actually is, why it stops or crashes, and how to tell the difference between an app pool problem and an application code problem.
How Linux file permissions actually work — the owner/group/other model, reading and writing permission strings, and the chmod/chown commands to change them safely.
The three pillars of observability explained plainly — what metrics, logs, and traces each tell you, and which one to reach for first depending on the question you're actually asking.
What makes a student portfolio project actually stand out to recruiters — depth over quantity, finishing over starting, and how to present projects so their value is obvious.
Why reading logs from the moment of failure backward, instead of scrolling forward from an arbitrary starting point, is faster and catches the real cause more reliably.
A practical, non-overwhelming approach to Windows Event Viewer — which logs actually matter, how to filter out the noise, and how to find the one entry that explains a crash.
A practical, repeatable framework for finding a real root cause instead of stopping at the first plausible explanation — the Five Whys, contributing-vs-root-cause, and writing a blame-free postmortem.
Practical credential hygiene for real projects — why secrets don't belong in source control, how .gitignore and environment variables actually protect you (and where they don't), and what to do if a secret is committed by mistake.
What actually happens during a TLS handshake, why certificate expiry breaks everything at once, and how to read the handshake yourself with openssl and a browser.
An honest picture of what a computer science degree really is before you start — problem-solving over memorization, why it's not just 'learning to code', and how to set the right expectations for four years.
CI/CD explained without the buzzwords — what continuous integration and continuous deployment actually automate, and what a real pipeline looks like end to end.
Why learning Git in your first year — long before any job — is one of the highest-return things a student can do, and how it doubles as a portfolio you build automatically.
What idempotent actually means for a deployment or automation script, why it matters when a script might be run twice by accident, and concrete patterns for writing scripts that are safe to re-run.
How to scope a final-year capstone so it's ambitious enough to matter but achievable enough to finish — the single decision that determines whether a capstone succeeds or becomes a mess.
Why memorizing syntax is the slow road and understanding what each line does is the fast one — how to read your first programs so the knowledge sticks.