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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Python Logging: A Practical Setup for Real Projects
A logging setup you can copy into a real project: why logging beats print, how loggers, handlers and levels fit together, one dictConfig that writes readable console output and a rotating log file, logging exceptions with tracebacks, adding request IDs, and keeping secrets out of logs.
Python Memory Management and Garbage Collection
How CPython decides when memory is freed: names and references, reference counting, the garbage collector that cleans up reference cycles, weak references, measuring memory with tracemalloc, trimming objects with __slots__, and the everyday patterns that make programs grow without limit.
Lookup and Get Metadata Activities in ADF
Lookup and Get Metadata are how an Azure Data Factory pipeline finds things out before it acts. This guide explains what each returns, the shape of their outputs, the documented limits of 5000 rows and 4 MB, and the patterns they enable: a loop driven by a control table, a watermark, a file check and a folder listing.
Deploying ML Models on AWS, Azure and GCP
AWS, Azure and Google Cloud all host models behind managed endpoints, but each expects a different serving contract. This guide runs one real model behind all three contracts locally, including Microsoft's own inference server, and shows what changes between clouds and what should stay exactly the same.
Python String Methods Every Developer Should Know
The string methods behind most real text work in Python, grouped by job (cleaning, splitting and joining, searching, comparing, checking) with the traps: strip removing characters rather than a suffix, split() versus split(' '), casefold, and why isdigit accepts characters int() rejects.
ADF Logging and Auditing for Compliance
An audit asks four things of a data pipeline: what ran, who changed it, what data moved and who had access. This guide maps each question to the record Azure Data Factory can produce, its retention, and the settings that must be on before the evidence exists, with a session log analysed as an example.