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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Building KPI Scorecards for Executives
How to build a KPI scorecard executives will actually use: how it differs from a dashboard, choosing a handful of balanced measures, writing definitions, owners, targets and red-amber-green rules, and a worked scorecard on real retail data that shows why a target that ignores seasonality turns every peak month green.
Service Accounts and Workload Identity on GCP
A pipeline cannot sign in with a password, so on Google Cloud it runs as a service account. This guide explains the kinds of service account, the five ways a workload proves it is one, why key files are the last resort, and how Workload Identity Federation lets GitHub Actions and GKE pods authenticate with no key.
Pipeline Orchestration: Airflow vs Prefect vs Dagster
Machine learning pipelines ask more of an orchestrator than nightly ETL: skipping expensive steps that have not changed, training many segment models with retries, and knowing which model came from which data. This guide runs those needs in Prefect and Dagster on real data, and maps them to Airflow.
Microsoft Fabric vs Azure Data Factory: What's New
Microsoft calls Fabric Data Factory the next generation of Azure Data Factory. This guide maps each Data Factory concept to its Fabric counterpart, lists what Fabric adds and what its documentation says is still missing, explains the move from pay-as-you-go to capacity billing, and sets out the three upgrade paths.
Glue Workflows vs Step Functions for Orchestration
Glue workflows and Step Functions can both run a multi-step pipeline on AWS, but one only knows about Glue and the other coordinates almost any service. This comparison covers what each can start, how they handle failure and reruns, how they are triggered and billed, and where managed Airflow fits as a third option.
Prometheus and Grafana for ML Monitoring
Prometheus and Grafana are the usual open-source pair for watching services. This guide instruments a real model API, scrapes it with Prometheus 3.15, unit-tests a drift alert, provisions a Grafana 13 dashboard from files and replays two real weeks of requests to see what the setup catches and what it misses.