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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Pydantic Explained: Data Validation in Python
Pydantic v2 shown on one realistic job, validating a payment webhook: how models convert and check types, field constraints, custom field and model validators, the structured errors it reports all at once, strict mode, parsing and producing JSON, and validating lists with TypeAdapter.
Python Data Structures: A Complete Reference
A reference to Python's data structures organised by the job each does best: the four built-ins, then deque for queues, Counter for counting, defaultdict for grouping, heapq for priorities and top-k, bisect for sorted lookups and namedtuple or dataclass for records, with the cost of each common operation.
Parameterizing Pipelines in Azure Data Factory
Parameters turn a pipeline that copies one table into a pipeline that copies any table. This guide explains the four places parameters live in Azure Data Factory, how a value travels from a trigger down to a connection, a worked generic copy in JSON, and where parameterising goes too far.
Async Programming in Python: asyncio Explained
What asyncio actually does, shown with runnable timings: why three one-second waits finish in one second, how tasks, gather and TaskGroup differ, how to add timeouts and a concurrency limit, and the single blocking call that silently makes async code sequential again.
Building a CLI Tool in Python with argparse
A step-by-step build of a small command-line tool with Python's argparse: positional arguments and typed options, choices and flags, subcommands, what happens on bad input, how to test the parser, and how to install the tool as a command with pyproject.toml.
Environment Variables and Secrets in Python Apps
A practical setup for configuration and secrets in Python applications: reading typed settings from environment variables and failing fast when one is missing, .env files that never reach Git, keeping secrets out of logs and Docker images, and what to do when a key leaks anyway.