1:1 mentorship with Durgesh Yadav · No batch, just you
Three months of live 1:1 classes. Then support until you're placed.
Two live one-to-one classes every week for three months, every Monday and Tuesday, 11 AM to 12 PM IST. When the classes end, the support carries on until you're placed.
₹59,999One fee for both phases: 12 weeks of classes, then support until placed.
Support runs until you're placed. It isn't a job guarantee.
The program at a glance
| Format | Live 1:1 video classes. You and your mentor, nobody else. |
|---|---|
| Schedule | Every Monday and Tuesday, 11 AM to 12 PM IST |
| Phase 1 | 12 weeks · 24 sessions · 24 hours of live 1:1 teaching and review |
| Phase 2 | From week 13 until you're placed |
| Track | Data Analytics: Excel, SQL, Python, statistics, Power BI, product analytics |
| Projects | 4 portfolio projects, each reviewed 1:1 and shipped to GitHub |
| Mock interviews | 2 in week 12, then more in Phase 2 as real interviews come up |
| Your time | 8 to 10 hours of practice a week outside the sessions |
| Fee | ₹59,999 |
The whole plan
WEEK 01 · Kickoff · Excel
Monday
S01 · Kickoff, baseline and setup
You leave with: A written goal, a working setup and your personal gap list.
Tuesday
S02 · Excel I: cleaning, formulas and lookups
You leave with: The formulas you will reach for every single week as an analyst.
This week's work: Clean a messy 5,000-row sales export (mixed date formats, duplicate orders, stray spaces), then pull product and region details in with XLOOKUP. Submit the workbook before Monday.
Checkpoint: You can take a raw export and make it analysis-ready without fixing rows by hand.
WEEK 02 · Excel · SQL
Monday
S03 · Excel II: pivots, Power Query and a one-page dashboard
You leave with: A dashboard that refreshes when next month's file lands.
Tuesday
S04 · SQL I: how a database thinks
You leave with: The practice e-commerce database loaded in MySQL and your first queries written.
This week's work: Finish the Excel dashboard for an imaginary regional manager (one page, four KPIs, two charts, slicers). Then write 25 filtering queries on the practice database.
Checkpoint: You can build a dashboard in Excel and answer a simple business question in SQL.
WEEK 03 · SQL
Monday
S05 · SQL II: GROUP BY, HAVING and CASE WHEN
You leave with: Comfort turning a plain-English question into a GROUP BY.
Tuesday
S06 · SQL III: joins without the fan-out
You leave with: The ability to read an unfamiliar schema and join it correctly.
This week's work: 30 aggregation and join questions on the practice database, sorted easy to hard. Under each answer, write one line on what a manager would do with that number.
Checkpoint: You can join across three or more tables and trust the totals.
WEEK 04 · SQL
Monday
S07 · SQL IV: subqueries, CTEs, dates and strings
You leave with: Long queries that read top to bottom, one step at a time.
Tuesday
S08 · SQL V: window functions
You leave with: Window functions you can write without looking anything up.
This week's work: Start Project 1: E-commerce SQL case study. It is due before Tuesday of week 5, so pace it across the week.
Checkpoint: You can rank, compare periods and build running totals in SQL.
WEEK 05 · SQL · Project 1
Monday
S09 · SQL VI: the patterns interviews keep repeating
You leave with: A pattern list you can spot inside any new question.
Tuesday
S10 · Project 1 review: E-commerce SQL case study
You leave with: Project 1 live on GitHub.
This week's work: 20 timed SQL interview questions in sets of five, 45 minutes per set. Write your reasoning under each one, not just the query.
Checkpoint: SQL module done. Goal: you can handle a medium-level SQL screening round.
WEEK 06 · Python
Monday
S11 · Python I: the parts analysts actually use
You leave with: Enough Python to follow an analysis notebook and change it.
Tuesday
S12 · Python II: pandas for analysis
You leave with: The ability to redo your SQL analysis in pandas.
This week's work: Recreate 10 of your Project 1 answers in pandas. Then start Project 2: food-delivery EDA. Load the data and list every problem you find in it. The full project is due before Tuesday of week 7.
Checkpoint: You can load, filter, group and merge data in pandas.
WEEK 07 · Python · Project 2
Monday
S13 · Python III: cleaning messy data and charting it
You leave with: A cleaning checklist you run on every new dataset.
Tuesday
S14 · Project 2 review: food-delivery EDA
You leave with: Project 2 live on GitHub.
This week's work: Finish Project 2 before Tuesday's review. After it, a statistics warm-up: mean, median and % change on your own food-delivery results.
Checkpoint: You can clean a messy dataset in Python and present what it says.
WEEK 08 · Statistics
Monday
S15 · Statistics I: describing data honestly
You leave with: The checks to question a number before you report it.
Tuesday
S16 · Statistics II: hypothesis tests and A/B testing
You leave with: The ability to read an A/B result and say ship, don't ship, or run longer.
This week's work: Analyse a checkout-page A/B test dataset: check the split is fair, run the test, and write a one-page recommendation a product manager could act on.
Checkpoint: You can explain a p-value to a product manager without jargon.
WEEK 09 · Power BI
Monday
S17 · Power BI I: from raw files to a data model
You leave with: A clean data model, ready for measures.
Tuesday
S18 · Power BI II: DAX, KPIs and report design
You leave with: A report a manager could open on Monday morning and use.
This week's work: Build Project 3: Business 360 dashboard in Power BI. Due before Monday's review.
Checkpoint: You can model data, write core DAX and design a report page.
WEEK 10 · Power BI · Product
Monday
S19 · Project 3 review: Business 360 executive dashboard
You leave with: Project 3 in your portfolio.
Tuesday
S20 · Product analytics, metrics and guesstimates
You leave with: A way to work through case and guesstimate rounds without freezing.
This week's work: Project 4: product analytics case study. Funnel, retention and an A/B readout on app event data, written up as a one-page memo. Due before Monday.
Checkpoint: You can diagnose a metric drop step by step.
WEEK 11 · Project 4 · Career
Monday
S21 · Project 4 review: product analytics case study
You leave with: Four projects, and a story for each.
Tuesday
S22 · Resume, LinkedIn, GitHub and the search plan
You leave with: A final resume, an updated LinkedIn and an application tracker.
This week's work: Send your first batch of applications and log them in the tracker. Revise SQL and Excel for Monday's mock.
Checkpoint: Portfolio and profile done. You are applying.
WEEK 12 · Mocks
Monday
S23 · Mock interview 1: technical round
You leave with: A fix list for the technical round.
Tuesday
S24 · Mock interview 2: case, guesstimate, HR and handover
You leave with: Two mocks done and a plan for your next 30 days of applications.
This week's work: Work through both fix lists and keep applying. From next week, every interview call you get goes to your mentor.
Checkpoint: Phase 1 complete. Placement support starts.
What you'll have to show
PROJECT 01 · Weeks 4-5 · reviewed in S10
The data: Practice e-commerce database: customers, orders, order items, products.
You ship: SQL file, README with findings, resume bullet
PROJECT 02 · Weeks 6-7 · reviewed in S14
The data: Messy food-delivery orders: missing ratings, mixed date formats, duplicate orders.
You ship: Jupyter notebook, charts, README, resume bullet
PROJECT 03 · Weeks 9-10 · reviewed in S19
The data: Retail sales, customers and products, modelled as a star schema.
You ship: pbix file, screenshots, 2-minute walkthrough video
PROJECT 04 · Weeks 10-11 · reviewed in S21
The data: App event data: visits, add-to-cart, checkout, purchase, plus an A/B test.
You ship: Analysis (SQL or Python) and a one-page memo
Phase 2 · week 13 onwards
Not yet? Fix it, then go again.
01
Stuck on an application, unsure about a role, or need a second look at something? Book a 1:1 call. The weekly Monday-Tuesday classes end with week 12; the mentorship doesn't.
02
Got a call? Send the JD. Before the interview you go through the role, that company's round pattern and the questions most likely to come up.
03
What they asked, where you lost marks, and what to fix before the next one. Over a few interviews this is where most of the improvement happens.
04
When real interviews line up, you get mocks aimed at that company's rounds, not a generic set.
05
Resume edits for specific openings, and review of your referral and recruiter messages.
06
Comparing offers, notice periods and joining dates, and how to negotiate without putting the offer at risk.
Straight talk on placement. Support runs until you're placed. It isn't a job guarantee: the offer comes from interviews you clear yourself, and the practice between sessions is yours to do. What doesn't stop is the help. Every interview you get, you walk in prepared and walk out with a debrief.
Fee and what's included
₹59,999
The fee covers the 12 weeks of live 1:1 classes and the placement support that follows, for as long as it takes.
Questions on eligibility, the curriculum or fit? Message Durgesh before you enrol.
Before you enrol
Your mentor
Durgesh Yadav
Data Engineer II at 7-Eleven · ex-Product Analyst, Target · Founder, PrepNPlaced
4.3 on Topmate · 503 ratings
Full profile300+ engineers Durgesh Yadav has personally mentored 1:1 have gone on to roles at top technology companies. This is Durgesh's personal 1:1 mentorship record, not a PrepNPlaced placement guarantee.
The plan, as a PDF
Common questions
Yes. SQL starts from SELECT in week 2 and Python starts from variables in week 6. What you need is time to practise, not a background.
Microsoft Excel (desktop), MySQL 8 with Workbench, Python through Anaconda/Jupyter or Google Colab, and Power BI Desktop. Power BI Desktop runs only on Windows, so if you're on a Mac, raise it in Session 1 and it gets sorted well before week 9.
Plan for 8 to 10 hours a week of practice and assignments on top of the two live hours.
No. Support continues until you're placed, but the offer comes from interviews you clear yourself. What this program guarantees is that you prepare for each of them with a mentor, and debrief after each one.
The Monday-Tuesday classes end and Phase 2 begins: mentor calls, company-specific prep, debriefs after every interview and more mocks, running until you accept an offer.
₹59,999. One fee covers both phases: the 12 weeks of live 1:1 classes and the placement support that follows.
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