IT Career Guides & Free Resources
Expert roadmaps, tutorials, salary guides and interview prep across Data Science, Generative AI, Python, Cloud & Analytics — written by GloryTecks trainers in Hyderabad.
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Data Science Roadmap 2026: A Complete Step-by-Step Guide
A data science roadmap in dependency order, from Python and SQL through cleaning, statistics and honest model evaluation to communicating results, with an exit test at every stage and one dataset that carries through the whole path.
What Is Generative AI? A Complete Beginner's Guide
What generative AI is, in plain language: how language models produce text one token at a time (shown with a tiny runnable model), how chat models are trained, how image models differ, what the technology is reliable for, and why it confabulates.
Learn Python from Scratch: A Complete 2026 Roadmap
How to learn Python from zero: install a current version (including the new Windows install manager), then work through seven stages, from values and loops to files, virtual environments, classes and tests, each ending with a small program you should be able to write on your own.
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Prompt Engineering: Techniques That Actually Improve Output
Most prompt advice is a list of tips. This guide takes one job, pulling three fields out of customer emails, and rewrites the prompt seven times, scoring each version on the same twelve emails. An example and a schema fixed the format; definitions and asking for evidence before the verdict fixed the meaning.
Spark vs Hadoop: What Changed and Why
What changed when Spark overtook Hadoop MapReduce: the three parts of Hadoop, the MapReduce model emulated step by step on three million taxi trips with its intermediate data written to disk, why in-memory processing and DAGs mattered, what Spark still borrows from Hadoop, and what that means today.
Incremental Data Loading in Azure Data Factory
Incremental loading copies only what changed since the last run. This guide explains the four approaches Azure Data Factory documents, builds the watermark pattern step by step, runs it on a real table to show what it catches and what it silently misses, and says when to use change tracking, dated folders or windows.
Statistics Interview Questions for Data Science
Statistics questions in data science interviews test judgement more than formulas. Eight common questions are worked here on 12,330 real online shopping sessions: skewed averages, standard error, p-values two ways, a bootstrap interval, a confounder in a weekend effect, multiple testing, outliers and sample size.
Window Functions SQL Interview Questions
Interviewers use window functions to see whether you understand how SQL evaluates a query, not just the syntax. These nine questions, each answered with a query run on two years of real bike rentals, cover ranking ties, top N per group, running totals, the default frame trap, gaps and islands, and filtering.
Migrating to BigQuery: A Practical Playbook
Moving a warehouse to BigQuery is less a copy job than a proof: that the SQL still means the same thing and the numbers still match. This playbook follows Google's iterative method, then reproduces two steps locally: a translator that gets one statement wrong, and a copy that passes row counts while 23 rows differ.