Free course · Career

Off-Campus Placements With AI

From Zero to Offer

A free, 44-article course for freshers in India who are looking for their first tech job without campus placement. It covers the whole search: an honest assessment of where you stand, proof of work, resume and LinkedIn, finding roles early, referrals, online assessments, interview rounds, offers and negotiation, and what to do when rejections pile up. AI is used throughout as a coach and checker, never as a ghostwriter.

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44
lessons: 11
modules: 7 h
of reading

Curriculum

11 modules · 44 lessons · about 7 h

Module 1Reality Check and Your Search Plan5 lessons · 1 h

Module 2Building Credibility From Zero5 lessons · 54 min

Module 3Resume and LinkedIn4 lessons · 41 min

Module 4Finding Jobs Before the Crowd4 lessons · 39 min

Module 5Applications and Referrals4 lessons · 38 min

Module 6Online Assessments and DSA4 lessons · 38 min

Module 7Company Research for Interviews3 lessons · 27 min

Module 8Technical Interview Rounds4 lessons · 40 min

Module 9Behavioral and HR Rounds4 lessons · 38 min

Module 10Offers, Negotiation and Joining4 lessons · 41 min

Module 11Rejection, Diagnosis and Momentum3 lessons · 28 min

This is a free course for people trying to land their first tech job off campus: final-year students whose college has few or no product-company drives, recent graduates who did not get placed, and people from other branches moving into tech. It walks through the whole search, from deciding where to aim to signing an offer, and shows how to use AI tools to do each step faster and better without inventing anything about yourself.

It is written for India, so it talks about Naukri, off-campus drives, service and product companies, CTC, PF and notice periods. Most of the method works anywhere.

Who it is for

Final-year engineering, BCA, MCA and B.Sc. students with no internship, or with an internship that will not convert.
Graduates of the last two or three years who are still searching, including those with a gap.
Students from non-CS branches (ECE, EEE, mechanical, civil) aiming at software roles.
Anyone targeting software developer (SDE) roles. Short notes cover data analyst, QA and support roles where their hiring process differs.

The idea that ties it together: the Search Loop

The whole course is one loop that you run every week:

Step	Question	Where you learn it
1. Target	Where should I aim, and how many applications does that need?	Module 1
2. Prove	What evidence can a stranger check in two minutes?	Modules 2 and 3
3. Reach	How do I get in front of a person, early, without spamming?	Modules 4 and 5
4. Clear	How do I pass the filters: screening and online assessments?	Module 6
5. Convert	How do I turn interviews into offers, and offers into a good decision?	Modules 7 to 10
6. Review	Which stage is leaking, and what one change fixes it?	Module 11, and every Sunday

Alongside the loop runs one honesty rule, the Follow-Up Test: never put anything in a resume, message or interview answer that you could not defend if someone asked one more question about it. It is the rule that decides how you use AI.

How the course uses AI

AI tools are useful in a job search: they can interrogate you until a vague story becomes a specific one, compare your resume with ten job descriptions, read a long offer letter, play a sceptical interviewer and spot patterns in your rejections. They are also good at producing confident, generic text and plausible facts that are wrong. So every article follows five ground rules:

AI asks, you answer. Use AI to pull out and organise your real details. Never let it invent a skill, a number, an achievement or a story.
Verify what matters. Anything about a company, a salary, a law, a tax rule or a date gets checked against a primary source before you rely on it.
No AI where it is not allowed. Do not use AI or any outside help during an assessment or a live interview unless the employer has said you may.
Redact before you paste. Remove Aadhaar and PAN numbers, phone numbers, addresses and other people's details before you paste anything into an AI tool.
Make it yours. Edit every draft until you would say it out loud in your own words.

Product names (ChatGPT, Claude, Gemini, Google AI Studio, NotebookLM, Perplexity and others) appear as examples of a kind of tool. Features, free limits and names change often, so check the current product before relying on a detail, and treat anything product-specific as true "as of October 2026". For a deeper grounding in using AI well, see the companion course AI From Zero to Productive: A Practical Guide to Using AI Well.

How the course is organised

There are 44 articles in eleven modules. Read Module 1 first, then go in order, or jump to the module for the stage you are stuck at.

Module	Articles	What it builds
1. Reality Check and Your Search Plan	Start Here: How Off-Campus Hiring Works, Honest Profile Assessment, Company Tiers and the Reach, Target, Safe Mix, Funnel Maths and Your Master Target List, Your Pipeline Tracker and 10-Week Plan	A realistic target, a list, a tracker and a plan
2. Building Credibility From Zero	Proof of Work, Choose and Build a Project, Deploy, Document and GitHub, Open Source, Hackathons and Writing, Honest Numbers	Evidence a stranger can check
3. Resume and LinkedIn	The ATS-Friendly Fresher Resume, Tailor Without Lying, LinkedIn for Freshers, Learn in Public and Network Early	Being findable and believable
4. Finding Jobs Before the Crowd	Where Fresher Jobs Appear, Alerts and Public Job Feeds, Funding News and Founder Signals, Fake Jobs and Recruitment Scams	A steady, safe flow of real openings
5. Applications and Referrals	How Referrals Work, The Referral Request, Cold Emails to Hiring Managers, Application Execution	Getting in front of people, respectfully
6. Online Assessments and DSA	Platforms, Formats and Rules, OA Strategy and Partial Scoring, Pattern-First DSA With AI, Company OA Research and the 48-Hour Plan	Passing the first filter
7. Company Research for Interviews	The 72-Hour Research System, JD, Blog and Product Research, Why This Company and Interview Day	Company-specific preparation
8. Technical Interview Rounds	Solve Out Loud, Machine Coding and LLD, System Design for Freshers, Mock Interviews	Clearing coding, design and live rounds
9. Behavioral and HR Rounds	Experience Inventory and Story Bank, STAR Stories With AI as Interrogator, Company Values and Follow-Up Pressure, Weakness, Failure, Conflict and the HR Round	Honest stories that survive questioning
10. Offers, Negotiation and Joining	Read Your Offer Letter, Fresher Offer Maths, Benchmark and Negotiate, Compare Offers and Prepare to Join	A good decision, not just a number
11. Rejection, Diagnosis and Momentum	Diagnose Your Funnel, Feedback and Self-Diagnosis, Course-Correct and Keep Going	Learning from every rejection

About the code

A few articles include short Python programs: a funnel calculator, a job-feed filter, a brute-force checker for assessment practice, a small low-level design, an in-hand salary estimate and a tracker report. Complete programs start with a comment such as # File: funnel.py and are followed by the output they printed when the course was written. They need Python 3.10 or later and no extra libraries. You do not need to run any of them to follow the course.

How to study

Read Module 1 first and finish its exercises. The target, list, tracker and plan you make there drive everything else.
Work on your own search, not on the examples. Every exercise has a version you can do with your own resume, list or story.
Attempt each exercise before opening its solution.
Keep one notes file for prompts that worked, stories, company research and lessons from rejections.
Run the Sunday review from Module 1 every week, even when nothing seems to be happening.

Must-know and nice-to-know

Must-know for everyone: Module 1, articles 6, 11 and 12 (proof of work and resume), 18 (scams), 20 (referral requests), 23 and 24 (assessments), 30 (solving out loud), 35 (STAR stories), 38 and 39 (offers) and 42 (diagnosing your funnel).
Core for product-company targets: articles 31 and 32 (low-level and system design), 19 to 21 (referrals and cold email) and Module 7.
Core for service-company targets: articles 23 and 26 (assessments and aptitude), 37 (HR round), 38 (bonds and service agreements) and 41 (joining delays and background checks).
Nice-to-know: article 16 (job feeds and automation), 17 (funding signals) and 33 (mock interview tools) once the basics are running.

Related courses on this site

For algorithms and data structures, DSA From Zero to Job-Ready: A Practical Guide with Java.
For design rounds, System Design From Zero to Interview-Ready.
For a backend stack and projects, Java From Zero to Job-Ready: A Practical Path from First Program to a Tested Spring Boot Backend.
For using AI well in general, AI From Zero to Productive: A Practical Guide to Using AI Well.

Honest limitations

Hiring practices differ between companies and change over time. Descriptions of rounds, platforms and tiers are typical patterns, not guarantees about any company.
Product features, free limits, laws, tax rules and salary data change. Where a figure matters, it is marked with a date and a source, and you should check the current official source.
The course gives general information. It is not legal, tax or financial advice. For a contract or tax question that matters, ask a qualified professional.
Nothing here promises a result. Your own tracker is the best evidence of what is working for you.

What you can expect

If you work through the course and do the exercises on your own search, you should be able to:

explain how off-campus hiring works and where your profile realistically stands;
choose a target mix of companies and work out how many applications that mix needs;
build proof of work a stranger can click on, and describe it with numbers you measured;
write a one-page resume and a LinkedIn profile that are easy to find and easy to trust;
hear about roles early, ask for referrals people can act on, and spot fake jobs;
prepare for online assessments, coding, low-level design, system design, behavioral and HR rounds;
read an offer letter, work out what an offer is really worth, negotiate and choose;
diagnose which stage of your search is failing and fix that stage.

What it cannot do: finishing this course does not guarantee interviews, an offer or a salary. Hiring depends on the market, the companies, timing and luck as well as on you. The course gives you a method that improves your odds, saves you from common and expensive mistakes, and helps you see what is and is not working. No statistic in it is presented as a promise, and the funnel numbers you will use are the ones you measure yourself.

How every article is built

Each article follows the same shape:

a short opening and a "Where this fits" note with the article number and what to read next;
the idea in plain words before any jargon;
worked examples with a goal, a first attempt, what went wrong, a better version and how to check it;
prompts you can copy, each with the checks that keep the output honest;
common mistakes;
three to five exercises, with full solutions that explain the reasoning;
links to what to read next.

Key takeaways appear in each article's summary box. People and companies in examples are illustrative unless a source is cited, and example AI responses are labelled as illustrative: yours will differ.

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Written by

Karthikeyan A

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