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.
RAG interview questions on chunking, retrieval and evaluation
RAG interview questions test whether you can find and fix the failure points in a retrieval-augmented generation pipeline: how documents are chunked, how chunks are retrieved and ranked, how the prompt uses them, and…
Quick-commerce dark store ops to data analyst: pick and ETA data
If you run shifts in a quick-commerce dark store, you already work with the data a retail or operations analyst studies: order timestamps, pick times, stock-outs and rider wait. Moving into a data analyst role means…
Quick-commerce delivery SLA by dark store: percentiles, not averages
Measure a dark store's delivery SLA as the share of delivered orders that arrived within the minutes promised to that customer at checkout, reported with the median and 90th-percentile delivery time. Then split each…
Questions to ask the interviewer in data and AI job interviews
The questions you ask at the end of a data science or AI interview do two jobs: they show the interviewer that you think about how work actually gets done, and they tell you whether the role is what the job description…
Questions to ask before paying for a data course, and evasive answers
Before you pay for a data course, ask twelve specific questions about money, time and people, and judge each answer by whether it is checkable. A good answer names a person, a number or a document you can read today. An…
Quantitative aptitude for placement tests: 12 questions solved
Quantitative aptitude in placement tests mostly checks a small set of arithmetic patterns under time pressure: percentages, ratios, work rates, speeds, averages, interest and simple counting. The fastest way to improve…
Quant analyst roles in India: research, risk and backtest hygiene
"Quant analyst" in India covers several distinct jobs that share mathematics and code: building pricing and risk models in banks' capability centres, validating other people's models, researching trading signals at…
How much Python do you need for AI engineering? A tiered answer
For AI engineering — building applications on top of language models — you need solid everyday Python rather than advanced tricks: functions and data structures, reading and writing JSON and files, calling HTTP APIs…
Python coding round for data roles, eight easy problems solved
Python coding rounds for data analyst and data scientist roles are usually easier than software engineering rounds: 30–45 minutes, one to three problems on dictionaries, strings, lists and sorting, often dressed up as…
Quiet study spaces in Delhi NCR for self-paced data practice
If your room in a PG or a shared flat is too noisy for self-study, Delhi Public Library runs a network of public libraries across Delhi, and many NCR learners also use their own college library or a paid reading room.…
Propose your first GenAI pilot at work on one page
A first GenAI pilot proposal should fit on one page and answer six things: the task, who does it today, what the tool would do, how you will measure the result, what data it touches, and when you will stop. Approvers…
Prompt engineering interview questions that test judgement
Prompt engineering interview questions now test judgement more than tricks: given two prompts for the same task, which is more likely to produce correct, consistent, checkable output, and how would you prove it? Strong…
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