Learn the work behind Data, AI & Forward Deployed Engineering
Practical explanations, career decisions and reproducible workflows. Read the reasoning, inspect the evidence and follow the next skill into a real programme.
Walk-in drives in Noida and Gurugram: how to vet one first
To vet a walk-in drive in Noida or Gurugram, confirm three things before you travel: that the company is registered and actually advertising this drive on its own channels, that the venue address matches a real office…
How to verify a data trainer's claimed industry experience
To verify a data trainer's claimed experience, check three things separately: that the employment history is consistent across public records, that the trainer can talk about real work at the level of detail…
Verbal ability in placement tests: a practice set with explanations
Verbal ability sections in placement tests check grammar, vocabulary in context, sentence order and reading comprehension. Most wrong answers come from a small number of rules — subject-verb agreement, fixed…
Reading a Variable Pay Plan: Individual × Company Multipliers
A variable pay plan turns your target amount into a payout using two or more factors, usually your rating and the company's result. Whether those factors are multiplied or weighted and added changes the payout more than…
20% Variable Pay in Your CTC: What Arrives Each Month
When 20% of your CTC is variable, your monthly salary is built from the other 80% only. The variable arrives, if it is earned, as a lump sum carrying all of its own income tax. For a hypothetical ₹15,00,000 CTC in tax…
Night-shift analytics roles in NCR: 12 questions before you accept
Before you accept a night-shift or US-shift analytics role in Noida or Gurugram, get written answers on the exact shift window, how you get home, how shift pay is shown on the payslip, how often the shift rotates, and…
UPI failure rates: separate customer declines from system declines
A UPI failure-rate analysis needs two denominators and one mapping table. Measure failures per attempt (what the rails saw) and success per payment intent (did the customer eventually pay), then map every response code…
UPI average ticket size from NPCI monthly data: a trend project
The average UPI payment has been getting smaller as UPI spreads into everyday small purchases, and you can measure that yourself from NPCI's own monthly figures. This project builds a clean monthly series of volume…
What Indians pay for on UPI: a merchant category code project
NPCI publishes monthly UPI merchant payments split by merchant category code (MCC), from groceries and fast food to fuel stations and pharmacies. That lets you answer a question most people only guess at: which kinds of…
UPI usage in Gautam Buddha Nagar, Ghaziabad and Gurugram districts
NPCI's UPI Statewise Statistics break usage down to the district. So you can ask a genuinely local question: how does UPI activity in Gautam Buddha Nagar (Noida and Greater Noida), Ghaziabad, Gurugram, Faridabad and…
Categorise UPI bank statement narrations with a rules table
To categorise a bank statement, first split each UPI narration into its parts (direction, reference, name, bank, VPA, note) with one regular expression, then apply an ordered rules table that matches patterns in a…
Rank banks by UPI downtime with NPCI incident data
NPCI publishes, for each period, which member banks had UPI downtime incidents, how many and for how long. This project turns that table into a small reliability pipeline. It snapshots the published figures into SQLite…
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