The CS Student Resume Guide: Every Section, Every Decision, With Real Before/After Examples

Your resume has about 6 seconds of attention from a recruiter before they decide to read on or move to the next one. In that time, they're looking for two things: recognisable tech keywords and evidence you've built real things.

Most student resumes fail on both. This guide fixes that.

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The Non-Negotiables

Before anything else: these rules are absolute.

1 page. You're a student or fresher. Two pages signal you don't know what's important. One page forces prioritisation — which is itself a signal of clear thinking.

ATS-friendly format. Applicant Tracking Systems parse your resume before a human sees it. Use a clean template with standard section headers (Experience, Education, Projects, Skills). No tables, no columns with text boxes, no graphics, no headers/footers. Use standard fonts (Calibri, Helvetica, Georgia).

PDF format. Never submit Word (.doc/.docx) — formatting breaks. Never submit an image. Always PDF.

No photo, no date of birth, no marital status. These are not required and create unconscious bias. Omit them.

Measurable results. Every bullet point that can be quantified should be. "Built a backend" is not impressive. "Built a REST API handling 500+ concurrent users with PostgreSQL and Redis caching, reducing response time by 40%" is.

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Section 1: Header

Your name, phone, email, GitHub, LinkedIn, and optionally a portfolio site. Nothing else.

PRIYA SHARMA
+91 98765 43210  |  priya.sharma@gmail.com  |  github.com/priyasharma  |  linkedin.com/in/priyasharma

Email: Use a professional address. priya.sharma@gmail.com is fine. priya.cutie.2001@gmail.com is not.

Phone: Indian format with country code is fine for Indian applications. Include +91 if applying internationally.

GitHub: Only include if your profile has at least 2-3 pinned repos with READMEs and recent activity. An empty GitHub is worse than no GitHub.

LinkedIn: Make sure your LinkedIn is complete and matches your resume before listing it.

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Section 2: Education

For freshers and students, education goes near the top.

EDUCATION

Indian Institute of Technology Kharagpur                    2021 – 2026
B.Tech, Computer Science and Engineering                    CGPA: 8.4/10

Relevant Coursework: Data Structures, Operating Systems, Computer Networks, 
Database Management Systems, Machine Learning

CGPA: Include if above 7.0. Below 7.0 — omit it and don't draw attention to it.

Relevant coursework: List only courses that align with the role you're applying for. Don't list "Physical Education" or "Communication Skills."

12th/10th marks: Omit once you're in 3rd year or beyond. Companies care about your engineering performance, not your school board results.

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Section 3: Projects (The Most Important Section)

For freshers, projects speak louder than internships. Every project should answer: what did you build, what tech did you use, and why does it matter?

The Formula

Project Name | Tech Stack                                   Month Year
[Deployed link] | [GitHub link]

• Built [what it does], achieving [measurable result]
• Implemented [specific technical feature], solving [specific problem]  
• Integrated [technology/API], enabling [capability]

Before/After Rewrites

Bad:

To-Do App                                                        2024
• Made a web application for managing tasks
• Used React and Node.js
• Added user login

Good:

Task Manager — Full-Stack Web App | React, Node.js, PostgreSQL, Docker   Mar 2024
github.com/priya/task-manager | task-manager-demo.vercel.app

• Built a full-stack task manager with authentication, real-time updates via WebSockets,
  and PostgreSQL persistence; achieved under 200ms response time under 100 concurrent users
• Implemented JWT-based auth with refresh token rotation, reducing session management
  overhead compared to server-side sessions
• Containerised with Docker Compose; deployed frontend on Vercel, backend on Render

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Bad:

ML Project                                                       2024  
• Built a machine learning model
• Used Python and sklearn
• Accuracy was good

Good:

Fake News Classifier | Python, scikit-learn, BERT, FastAPI            Nov 2024
github.com/priya/fake-news-classifier

• Fine-tuned BERT on 44,000+ news articles; achieved 94% accuracy on the LIAR dataset,
  outperforming baseline TF-IDF+SVM model (88%) by 6 percentage points
• Exposed model as REST API using FastAPI with under 300ms inference time per request
• Deployed on Hugging Face Spaces with a Gradio demo interface (2,000+ monthly users)

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How Many Projects?

• 2-3 strong projects beats 6 weak ones
• Each project should use a different area of tech (one backend, one ML, one systems/algorithms)
• At least one project should be live/deployed with a real URL

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Section 4: Experience / Internships

If you have relevant experience:

EXPERIENCE

Software Engineering Intern | Startup X                      May – Jul 2024
• Developed REST API endpoints for user notification service using Node.js and Redis pub/sub,
  supporting 10,000+ daily active users
• Reduced page load time by 35% by implementing server-side caching with Redis and moving
  static assets to CloudFront CDN
• Wrote 45+ unit tests using Jest, increasing code coverage from 62% to 87%

Quantify everything possible. "Wrote unit tests" is weak. "Wrote 45+ unit tests, increasing coverage from 62% to 87%" shows precision and impact.

If your internship wasn't technical (IT support, data entry):

• Include it but put it below projects
• Focus on any technical tasks you did ("Automated report generation with Python, saving 3 hours/week")

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Section 5: Technical Skills

TECHNICAL SKILLS

Languages:    Python (proficient), Java (intermediate), JavaScript/TypeScript, SQL, C++
Frameworks:   React, Next.js, Node.js/Express, FastAPI, Spring Boot
Databases:    PostgreSQL, MongoDB, Redis
Tools:        Git, Docker, AWS (EC2, S3), Linux, Postman, Figma
Concepts:     REST APIs, Microservices, System Design, Data Structures & Algorithms

Rules:

• Only list what you could discuss for 5 minutes in an interview
• Don't list "C" because you took an intro course 2 years ago — omit it
• "Proficient / Intermediate / Familiar" labels are optional but helpful
• Don't list "MS Office," "Google Docs," or similar — these are not tech skills
• Order by proficiency: strongest first within each category

About listing CGPA-type achievements vs skills: Competitive programming achievements (ICPC, CodeChef ratings) should go in an "Achievements" section if strong, not the skills section.

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Section 6: Achievements and Extra-Curriculars

Only include if genuinely strong:

ACHIEVEMENTS

• LeetCode: Solved 300+ problems, Knight badge (top 5%)
• Codeforces: Rating 1650 (Expert), ranked in top 15% globally
• Google STEP Intern 2023
• GATE 2024: AIR 850 (score 72.4)
• Best Project Award, IIT Kharagpur Hackathon 2023 (1st among 120 teams)

Don't include:

• Participation certificates
• School achievements (unless very recent — board topper, national olympiad)
• "Certificate of completion" from online courses (dozens of students have these — they add no signal)
• "Best student award" from your department unless it's genuinely prestigious

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The One-Page Rule: How to Cut

If you can't fit everything in one page:

1. Cut weakest project first
2. Remove irrelevant coursework
3. Reduce bullet points per project from 4 to 3
4. Reduce school achievements to only top 2
5. Remove irrelevant skills (don't list 20 technologies to look impressive)

If you still can't fit it: your margins are too generous (use 0.5" margins) or your font is too large (10pt is acceptable for body text).

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The Final Checklist

Before submitting any resume:

• [ ] Saved as PDF, not Word
• [ ] Name is correct in the filename (PriyaSharma_Resume.pdf)
• [ ] All links work (GitHub, LinkedIn, project demos)
• [ ] Every project has tech stack listed
• [ ] At least one number/metric in each project description
• [ ] No typos (spell-check + read aloud)
• [ ] Skills section only lists things you know well
• [ ] No photo, DOB, or marital status
• [ ] Exactly 1 page
• [ ] Font is standard and legible at 10-12pt

Before applying: Run your resume through the JD Analyser. Paste the JD for your target role alongside your current skills, and it'll tell you exactly which keywords and skills to highlight for that specific application.