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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Looker and Looker Studio on GCP Explained
Google has two BI tools with similar names and different jobs. Data Studio, the new name for Looker Studio, builds self-service reports at no cost. Looker adds a central model that defines each metric once. This guide compares them and uses a real database to show the mistake a shared model prevents.
Materialized Views in BigQuery Explained
A materialized view stores the result of a query and keeps it current as the base table changes. This guide shows how BigQuery combines stored results with new rows, models it on 2.9 million real trips, and covers refresh settings, max_staleness, smart tuning, unsupported SQL and when a scheduled table is better.
Computer Vision Basics: From Pixels to Predictions
Computer vision from the ground up: what an image is to a computer, how a convolution filter finds edges, a small convolutional network trained on handwritten digits against a pixel baseline, the main vision tasks from classification to segmentation, and why transfer learning is the default.
NumPy Interview Questions for Data Roles
NumPy questions check whether you understand what an array really is: a block of typed memory with a shape. Ten questions, answered on 1,599 real wine samples with NumPy 2, cover axes, views versus copies, broadcasting, silent integer overflow, NaN, float comparison, ties in top-N, vectorisation and seeds.
Evaluating LLM Outputs: Metrics, Tools and Best Practices
Every change to a prompt or model needs evidence that it helped. This guide explains the main ways to evaluate LLM outputs, then checks a small local LLM judge against expert human verdicts from MT-Bench and finds it agreeing often, flipping often when answers swap places, and trustworthy only when consistent.
Loading Data into BigQuery: Batch and Streaming
BigQuery can be loaded in batches from files or fed continuously through the Storage Write API. This guide compares the methods by latency, cost, limits and what a retry does, with documented commands, a model of at-least-once against exactly-once delivery, and a rule for choosing.