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.
Trending This Week
Data Scientist Salary in Hyderabad 2026: How Pay Grows From Fresher to Senior
Data Science · 7 min
ChatGPT Complete Guide: Features, Prompts and Use Cases
Generative AI · 5 min
Python Interview Questions: Top 50 with Answers
Python · 10 min
DAX Guide: Measures, Calculated Columns and Context
Power BI · 6 min
All articles
PySpark Tutorial: DataFrames, Transformations and Actions
A practical PySpark DataFrame tutorial on three million real New York taxi trips: declaring schemas, filtering and deriving columns with when and otherwise, grouped aggregation that exposes a trap in tip data, a join and a window function for top zones per borough, the same logic in Spark SQL, and the actions.
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.
Pandas Interview Questions Every Analyst Should Know
Pandas interview questions are rarely about remembering method names. They check whether you notice what the data and the library do quietly. Eight questions answered on 41,188 real bank marketing calls with pandas 3: disguised missing values, agg vs transform, groupby and NaN, copy-on-write, merges, pivots, bins.
Scaling Model Training with Distributed Computing
Distributed training splits the work across machines, but keeping them in step costs time. In real PyTorch data-parallel runs with one, two and four workers, every replica stayed identical, yet small batches trained slower with more workers and only large batches gained, about one and a half times with four.
Tokenization in LLMs: Why It Matters More Than You Think
Models do not read words. They read tokens, and tokens decide what a prompt costs, how much fits in the context window and why a model stumbles on spelling and long numbers. This guide explains subword tokenization and measures it: one sentence is 8 tokens in English and up to 99 in Telugu.
How to Handle Multiple Job Offers Gracefully
Two offers at once is a good problem, but easy to handle badly: deadline pressure, awkward conversations and the temptation to accept one and keep looking. Using US college-recruiting guidance on offer deadlines and good-faith acceptance, this guide shows how to decide and communicate well.