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 Cleaning: A Practical Step-by-Step Guide
A step-by-step data cleaning guide on 541,909 real transaction lines: profiling before touching anything, removing duplicates, standardising messy text, fixing inconsistent categories, investigating extreme values, keeping a cleaning log, and validation checks that caught a problem the cleaning itself created.
Docker for Machine Learning: A Practical Guide
How to containerise a machine-learning project so it runs the same everywhere: pinning the exact library versions a saved model depends on, a Dockerfile ordered for fast rebuilds, keeping data out of images, multi-stage builds, non-root users and GPU access.
Power BI Dashboard Design: A Practical Guide
Designing Power BI reports and dashboards: the difference between the two in the Power BI service, planning for the audience, laying out a page, choosing visuals and formatting numbers the way Microsoft recommends, interactions and navigation, accessibility, performance, and a checklist to review any page.
Feature Engineering: A Practical Guide with Examples
Feature engineering, measured step by step on 17,379 hours of real bike-rental data: how encoding the hour, adding an hour-by-working-day interaction and two domain features cut a linear model's error from 131 to 73 rentals, why the same features hurt a tree model, and the leakage rules every new feature must pass.
How to Switch Careers After 30: A Practical Guide
People do move into tech after 30, though they are a small minority, and once there they are as satisfied as everyone else. Survey data from nearly 29,000 working developers and data professionals shows how common late starts are, which roles late starters hold, and what a realistic switch looks like.
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.