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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Shadow Deployment and Canary Releases for ML
Shadow mode runs a new model on real traffic without letting it answer; a canary lets it answer for a few users first. On real e-commerce sessions, this guide shows a unit bug that 89% agreement hid, the flag-rate guardrail that caught it, and why per-stage business metrics were too noisy to gate on.
Building Confidence for Technical Interviews
Interview nerves are not the problem; how you interpret them is. Experiments show people who reframe anxiety as excitement perform better than those who try to calm down, and interview data shows candidates are poor judges of their own performance. This guide turns that into a routine.
AWS Cloud Practitioner Certification: How to Start
The AWS Certified Cloud Practitioner is AWS's foundational certification. This guide uses the official CLF-C02 exam guide to explain who it is for, the exam's format, cost and passing score, the four domains and what each asks, what is out of scope, a study plan for beginners, and when it makes sense to skip it.
Cross-Validation in Machine Learning: A Practical Guide
Cross-validation done properly: what cross_val_score does by default, how to pick the splitter your data actually needs (stratified, grouped or time-ordered), and a runnable demonstration of how preprocessing outside a pipeline turns random noise into an 85% score.
AWS CloudWatch for Monitoring Data Pipelines
Monitoring a data pipeline means knowing when it failed, when it did not run, and when it ran but produced bad data. This guide shows how Amazon CloudWatch covers all three: the metrics worth publishing, alarm settings including missing data, logs, EventBridge events from Glue, and a worked example in boto3.
Migrating Data to AWS: DMS and Best Practices
AWS Database Migration Service copies databases into AWS and keeps them in step with ongoing changes. This guide explains its components, the three task types, what DMS writes to S3 for a data lake, how to turn its change records into a current table on real data, and the documented practices for load and validation.