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.
Trending This Week
Data Scientist Salary in Hyderabad 2026: How Pay Grows From Fresher to Senior
Data Science · 7 min
ChatGPT Complete Guide: Features, Prompts and Use Cases
Generative AI · 5 min
Python Interview Questions: Top 50 with Answers
Python · 10 min
DAX Guide: Measures, Calculated Columns and Context
Power BI · 6 min
All articles
List Comprehensions in Python: A Complete Guide
Everything about list comprehensions in one place: how the syntax maps to a loop, where if and if-else go (and the SyntaxError when they are swapped), nested loops in the right order, dict and set comprehensions, generator expressions for large data, the walrus operator, and the point where a plain loop reads better.
Python Best Practices: Writing Pythonic Code
What "Pythonic" means in practice, as before-and-after pairs you can run: looping with enumerate and zip, unpacking, dictionary and Counter idioms, building strings, checking None and emptiness, handling files, plus naming, function design and the formatter, linter and type checker that keep code consistent.
Python Decorators Explained with Real Examples
Decorators demystified: what the @ line actually does, why functools.wraps matters, and five decorators worth writing or knowing, from a timer and a configurable retry to functools.cache, a registry that collects plugins, and a permission check, plus the order in which stacked decorators run.
Python Decorators vs Context Managers: When to Use Each
Decorators wrap a whole function; context managers wrap a block of code. How each one works, a transaction that rolls back on error, a single timer usable as both a decorator and a with statement, suppress and ExitStack from contextlib, and a clear rule for choosing between them.
Python f-Strings: Formatting Done Right
A practical tour of what goes after the colon in a Python f-string: alignment and width, thousands separators, decimal places and percentages, signs and padding, dates and times, repr and the = debugging specifier, nested specs for dynamic widths, and building aligned text tables.
Python Generators and Iterators Made Simple
How iteration really works in Python, from the protocol behind every for loop to generator functions with yield: building lazy pipelines that process a file of any size in constant memory, delegating with yield from, the itertools functions worth knowing, and the one-shot behaviour that surprises everyone once.