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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Amazon S3 Explained: Storage, Classes and Best Practices
How Amazon S3 storage classes differ — minimum storage duration, minimum billable size, retrieval time — and a four-question method for putting each dataset in the right class, with lifecycle and security defaults for a data-engineering bucket.
Production ML Systems: Architecture and Best Practices
In a production machine learning system the model is the smallest part. This guide maps the components around it, compares the three serving patterns, explains the ML-specific technical debt that architecture has to contain, and sets out the practices that keep a system maintainable as it grows.
Best Programming Languages for Data Science in 2026
Which programming languages data science work actually uses and why: SQL and Python as the core pair, R for statistics, Scala and Java around Spark, Julia for numerical work, and JavaScript for interactive charts, with the same analysis written in SQL and Python and a learning order by role.
BigQuery Best Practices for Analysts
An analyst can go wrong in BigQuery in three ways: a wrong number, a wasted scan, or a result nobody can reproduce. This guide gives a routine for each, with four correctness checks on 2.9 million real trips: NULL counts, filters that lose rows, days that shift with the time zone, and a join that adds rows.
Best Free Datasets for Data Science Practice in 2026
Free datasets for data science practice, organised by the skill you want to build: built-in data for learning algorithms, public-sector data for cleaning, large trip records for performance, text and image collections, dataset search engines, and a checklist for licence and quality.
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.