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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Personal Projects That Double as Interview Stories
A personal project helps in an interview only if you can tell a good story about it: a real decision, a setback, a result. Employers say they want examples of skills used to solve problems. This guide shows how to plan projects so they produce those moments, keep a log while you work, and turn them into answers.
S3 Lifecycle Policies and Storage Cost Savings
S3 Lifecycle rules move objects to cheaper storage classes and delete them on a schedule. This guide explains transition and expiration actions, builds a three-rule configuration for a data lake bucket with boto3, and sets out the charges that catch people out: small objects, minimum durations, versions and archives.
AWS Glue vs EMR vs Lambda for ETL
Glue, EMR and Lambda can each run ETL code on AWS, and they are built for very different sizes of job. This comparison sets out the hard limits of each, how data volume, control and operations decide the choice, how each is billed, and why most real pipelines end up using two or three of them together.
Power BI Deployment Pipelines for Teams
How Power BI teams use deployment pipelines: stages and capacity requirements, which items can be deployed, item pairing and the duplicates it can create, deployment rules that point each stage at the right data, why data needs refreshing after deployment, and a team workflow.
PySpark vs Pandas: When to Use Which
When to use PySpark and when to use pandas: the same hourly revenue query written in both and checked to give identical answers on three million taxi trips, the eightfold memory cost of loading the data into pandas, eager versus lazy execution, Arrow and toPandas, pandas API on Spark, and a decision guide.
From Python Beginner to Job-Ready: A 6-Month Plan
A six-month Python plan only works if you can tell, each month, whether you are on track. This plan gives a weekly focus for each month and one checkpoint exercise you should be able to write from scratch by its end. All six are solved here on real data, from the Zen of Python to two years of bike rentals.