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.
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Data Flow Debug and Performance in ADF
Debug mode lets you watch a data flow work on live data, and it bills like a running cluster. This guide covers what debug does and does not check, the four places a data flow loses time, cluster size and time to live, partitioning and skew measured on real data, and the pipeline designs that waste clusters.
From Data Scientist to MLOps Engineer: A Roadmap
Data scientists already know models, data and evaluation, which is most of what MLOps engineers wish their colleagues knew. The gap is software and operations. This plan sets out what transfers, what to learn, a twelve-week sequence built around one evolving project, and how to present the move to employers.
Data Preprocessing: Cleaning Data the Right Way
Preprocessing for machine learning without score-inflating mistakes: splitting before anything learns from data, imputing while recording what was missing, standard versus robust scaling, encoding categories unseen in production, and one ColumnTransformer pipeline for all of it.
Data Science Internships in Hyderabad: How to Land One
A practical plan for getting a data science internship, for students and freshers in Hyderabad and elsewhere: the skills interns are actually tested on, projects that stand out, where openings are posted, applications that get replies, what intern interviews check, and how to turn an internship into an offer.
Exploratory Data Analysis (EDA): A Step-by-Step Walkthrough
Exploratory data analysis done step by step on the Titanic passenger list in pandas, with every number from real runs: what a row means, missing values that predict the outcome, a fare column that is really a group price, relationships a correlation misses, and two columns that would leak the answer into any model.
From Data Analyst to Data Scientist: A Transition Roadmap
A transition roadmap for working data analysts who want to become data scientists: what you already have that newcomers lack, the five gaps to close, a phased plan where each stage ends in a piece of work from your current job, how to reposition your CV, and the traps that slow most people down.