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.
Featured Guides
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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Top Python Libraries Every Developer Should Know
A map of the Python libraries that come up again and again in real projects, grouped by job: standard-library modules to learn first, then HTTP clients, web frameworks, data and machine learning, validation, databases, testing, command-line tools and code-quality tooling, and how to choose.
Connecting ADF to REST APIs and Web Sources
Azure Data Factory has four ways to talk to a web endpoint, and choosing the wrong one is the usual first mistake. This guide separates the REST connector, the HTTP connector, the Web activity and the Webhook activity, explains pagination rules with a working simulation, and lists the documented limits.
Web Scraping with Python: BeautifulSoup and Requests
A practical, responsible introduction to web scraping in Python: fetching pages with Requests and a proper session, parsing HTML with Beautiful Soup and CSS selectors, extracting tables and following pagination, checking robots.txt, rate-limiting, and recognising when an API or a browser tool is the better option.
Working with JSON in Python: A Practical Guide
A practical guide to JSON in Python with the json module: how Python types map to JSON and what does not survive a round trip, reading and writing files, pretty and compact output, serialising dates and Decimals, keeping money exact when parsing, understanding decode errors, JSON Lines for large data, and the NaN trap.
Virtual Environments in Python: venv, pip and Poetry
Why every Python project needs its own environment, and how to manage one: creating and activating a venv, installing and pinning packages with pip, reproducing an environment exactly from a requirements file, the difference between direct and locked dependencies, and when a tool such as Poetry or uv is worth adopting.
Unit Testing in Python with pytest: A Beginner's Guide
A beginner's guide to pytest built on a small real module: writing tests as plain functions with assert, reading pytest's failure reports, parametrising edge cases, testing that errors are raised, and using fixtures, tmp_path and monkeypatch so tests never touch real files or settings.