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 Interview Questions for Data Roles
The plain-Python coding tasks data-analyst and data-engineer interviews use, without pandas: counting, deduplicating, grouping, streaming large files, flattening JSON, joining, and the bugs interviewers plant. Each has a worked solution and the follow-up questions to expect.
Python for Data Science: The Essential Libraries
The Python data science stack explained by the job each library does: NumPy for arrays, pandas for tables, Matplotlib and seaborn for charts, SciPy and statsmodels for statistics, scikit-learn for models and Jupyter for exploration, with one runnable example that passes a real dataset through them.
RAG Architecture Explained: Retrieval-Augmented Generation
RAG gives a language model the right pages to read before it answers. This guide walks through the four stages with a pipeline that runs on a laptop, using open models and public documents, and shows three outcomes: a correct cited answer, a retrieval miss the model admits to, and a question outside the documents.
Power Query Tutorial: Transforming Data Without Code
A working tutorial for Power Query in Power BI Desktop: the applied-steps model, the profiling setting that hides problems, data types, the unpivot option that survives refresh, query folding, and how to structure queries so a report still refreshes next month.
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.
Data Warehouse Explained: Concepts and Architecture
A clear explanation of data warehouses: why analytical queries need a separate store from transactional systems, the architecture from sources through staging, modelled layers and a semantic model, facts, dimensions, grain and history, modelling approaches, modern platforms and common pitfalls.