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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Amazon EMR Explained: Big Data on AWS
Amazon EMR runs Spark, Hadoop, Hive and other big data frameworks on AWS. This guide explains primary, core and task nodes, why data belongs in S3 and not in the cluster's HDFS, how work is submitted as steps, transient versus long-running clusters, the Serverless and EKS options, and what decides the bill.
AI Coding Assistants: How to Use Them Effectively
AI coding assistants write plausible code quickly, and plausible is not the same as correct. This guide summarises what research says about their speed and security, then has a small local model write six functions, scores them with hidden tests, and shows what examples and test feedback fix.
Building AI Agents with LangGraph: A Hands-On Tutorial
Agent tutorials stop when the demo works. Production agents fail in other ways: tools time out, loops never end, and behaviour changes silently. This hands-on guide builds a small LangGraph agent and makes it reliable, with a retry policy on its tool node, a recursion limit and deterministic tests.
What Is MLOps? DevOps for Machine Learning Explained
MLOps is the practice of building machine learning systems that keep working after launch. This guide defines it, explains why ML needs more than DevOps, and shows the problem it solves on real data: a model built in 2011 that was 38% wrong through 2012, and how much the way you retrain it matters.
How to Make a Career Pivot Without a Pay Cut
Pay cuts in a career pivot usually come from moving too far at once. Using the US Department of Labor's skill ratings, this guide measures how much of three data roles eight common jobs already cover, shows the specific gaps to close, and explains the adjacent and internal moves that protect your salary.
Building a Real-Time Dashboard with GCP
A real-time dashboard is a chain, and it is as fresh as its slowest link. This guide builds one on Google Cloud, from events in Pub/Sub to a per-minute table in BigQuery and a report in Data Studio, and replays an hour of real events to show why recent numbers change after they first appear.