Freshers
Turn projects, internships, SQL practice, and mock rounds into clearer proof before applying.
01Resume Suite
Score, rewrite, edit, compile, and download from one place.
Resume Lab checks role fit and proof gaps. Resume AI creates a JD-aligned LaTeX draft, lets you apply requested edits in the same template, then compiles a clean PDF.
Locked template
Anti-fabrication guardrails
Editable LaTeX source
PDF + .tex export
Resume intelligence pipeline
score · rewrite · source · compile
Fit signal 86
Score against JD
ATS fit, missing keywords, proof strength, and recruiter-readable gaps.
Grounded 82
Rewrite with evidence
Improve bullets without inventing claims or breaking source truth.
Template Locked
Edit LaTeX source
Locked template, editable source, clean structure, and review notes.
PDF Ready
Compile + export
Generate a PDF, download the .tex, and keep the output ready to apply.
02Live Mock Engine
Practice the rounds that actually decide tech offers.
CareerOS combines role-specific interview intelligence, real coding tests, system design whiteboarding, and voice follow-ups in one live room.
live stackCompiler-backed
DSA + coding rounds
Fill-the-function prompts, compiler tests, complexity follow-ups, and AI code review.
Architecture
System design whiteboard
Requirements, APIs, data model, services, data flow, scale limits, and tradeoffs.
Targeted
Role-aware questions
Backend, full stack, data, Java, Python, SRE, and systems tracks adapt live.
Live voice
Voice interview flow
One realistic question at a time, voice follow-ups, and quiet coding windows.
Rubric scored
Grounded evaluation
Feedback reflects test results, project depth, communication, edge cases, and design reasoning.
Data ready
Data-role practice
Data Analyst and Data Engineer paths include Pandas and PySpark-style review.
The Loop
One connected loop, from target company to offer.
Every step feeds the next. The same target role threads resume, job search, applications, visibility, and interview prep, so you always know the next move.
- 01
Check target company
Start with the company, role, and hiring loop you actually want to win.
- 02
Check resume ATS
Score your resume against the target and identify gaps before applying.
- 03
Rebuild if score is low
If the fit score is weak, rebuild a truthful resume with stronger proof.
- 04
Search by resume + freshness
Find jobs that match your real resume, role intent, location, and recency.
- 05
Fetch live jobs
Pull fresh roles from job boards, ATS/company pages, and live source signals.
- 06
Apply with automation
Use the supervised Auto Apply workspace to move faster without hiding the browser.
- 07
Post on LinkedIn
Turn preparation, projects, and learning proof into recruiter-facing content.
- 08
Increase calls
Keep improving resume, job fit, and public proof until outreach quality rises.
- 09
Got a call? Practice rounds
Generate role and company-style interview rounds before the actual screen.
- 10
Shortlisted? Salary standards
Use salary benchmarks and offer context to prepare the next conversation.
04Who It's For
One target role, connected across resume, jobs, learning, and interviews.
PrepNPlaced is designed for candidates who need a practical preparation loop — not disconnected tools that forget the role they are targeting.
Career Switchers
Use resume gaps and target JDs to decide what to learn, what to build, and what to practice next.
Data Analysts
Connect SQL, Excel, Power BI, Python, dashboards, and business metrics to role-specific resumes and interviews.
Data Engineers
Prepare SQL, Python, PySpark, ETL, data modeling, pipeline debugging, and project deep dives in one loop.
Software Engineers
Practice coding, system design, project ownership, and resume evidence against a target company or role.
Indian Tech Candidates
Plan preparation around real interview rounds, JD requirements, notice period, role fit, and application readiness.
05Career Guides
Explore the PrepNPlaced workflows by outcome.
Public guides explain each workflow before you enter the private CareerOS workspace.
Ready When You Are
Start with the hub, then move into a real mock interview.
Turn the same resume, role, and JD context into intelligence, resume improvements, live mock practice, and a clear final report.
Role-aware rounds
Compiler-backed coding
System design board
Prep system status
hub · resume · mock room
Target Brieflinked
Resume AIlinked
Live Mocklinked
Student Outcomes
Students from non-tech backgrounds, now placed at top MNCs as data professionals.
Built from the placement portfolio. These brand cards keep the proof visible without interrupting the CareerOS product story.
Placement Records
Placement wins from learners who switched into data careers.
Real career switches from operations, mechanical, support, beauty, EduTech, and service-company backgrounds into data roles.
0K+
Total followers across channels
0K+
Learners trained and supported
Top 0%
WhatsApp and Telegram communities
Pragya Rathi
7-Eleven
Non-Tech Background → Data Engineer
Previous
Non-Tech Background
Placed as
Data Engineer
Career switch LinkedIn
Gautam Kumar
PrepNPlaced
Struggling To Get Placed → Data Analyst
Previous
Struggling To Get Placed
Placed as
Data Analyst
Career switch LinkedIn
Harsohrab Singh
Werize
Freelancing → Product Analyst
Previous
Freelancing
Placed as
Product Analyst
Career switch LinkedIn
Senthilkumar
Deloitte
Operations & Accounts → Data Analyst
Previous
Operations & Accounts
Placed as
Data Analyst
0% hike LinkedIn
Ritesh Gandhare
Infor
Mechanical Field → Data Analyst
Previous
Mechanical Field
Placed as
Data Analyst
0% hike LinkedIn
Sneha Kulkarni
7-Eleven
Zero Experience + Career Gap → Data Engineer
Previous
Zero Experience + Career Gap
Placed as
Data Engineer
0% hike LinkedIn
Lipika Gupta
Target
EduTech Domain → Data Analyst
Previous
EduTech Domain
Placed as
Data Analyst
0%+ hike LinkedIn
Bindu Bharti
Physics Wallah
Beauty Brand → Data Analyst
Previous
Beauty Brand
Placed as
Data Analyst
0%+ hike LinkedIn
Om Rai
People INC.
Service-Based Company → Data Analyst
Previous
Service-Based Company
Placed as
Data Analyst
0%+ hike LinkedIn
Pallavi Oja
Deloitte
Support Role → Data Analyst
Previous
Support Role
Placed as
Data Analyst
0%+ hike LinkedIn
Anala Rajesh
Target
PwC → Senior Data Analyst
Previous
PwC
Placed as
Senior Data Analyst
0%+ hike LinkedIn
Mohit Dudeja
Wells Fargo
Ericsson → Data Analyst
Previous
Ericsson
Placed as
Data Analyst
0%+ hike LinkedIn
Trusted mentor, real ratings
4.6★ from 1,000+ learners · 100K+ learners mentored
Data Engineer @ 7-Eleven · ex-Target · Instructor @ Scaler & Bosscoder
Co-founded & mentored by Durgesh Yadav & Pragya Rathi — a 4.9★ co-mentor across 127 live classes.
4.85/5
Bosscoder
4.7/5
Newton School
4.3/5
Topmate
Durgesh isn't just a mentor, he's more like a brother to me. His wisdom and kindness have taught me things money can't buy. I've grown so much under his guidance — he knows how to make it click for each person individually.
An amazing, eye-opening experience for anyone confused as a fresher or experienced person about what to learn or which domain to switch into. Durgesh gave a clean, clear view, understood everything with patience, and shared very useful tips to crack companies within 3-4 months.
Learning with PR as my SQL trainer has been an absolute game-changer. As a complete novice I approached SQL with trepidation, but her expertise, patience and dedication transformed my experience entirely — a rare combination of deep knowledge and the ability to make it click.