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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Experiment Tracking: MLflow vs Weights & Biases
MLflow and Weights & Biases are the two most common ways to track machine learning experiments. This comparison logs the same runs to both with almost identical code, shows where each keeps the data, and sets out the real differences: hosting, licence, collaboration, hyperparameter search and lock-in.
Amazon MSK: Managed Kafka on AWS
Amazon MSK runs open-source Apache Kafka for you on AWS. This guide explains what the service manages and what remains your job, Provisioned clusters with Standard or Express brokers versus Serverless, MSK Connect and Replicator, authentication choices, tiered storage, and how to choose between MSK and Kinesis.
Redshift Performance Tuning: Distribution and Sort Keys
Redshift performance tuning starts with two table properties: how rows are distributed across slices and how they are sorted on disk. This guide explains the four distribution styles and the sort key options, simulates block skipping and slice skew on 2.96 million real rows, and shows when AUTO is the right answer.
Kaggle for Beginners: How to Start and Win Medals
Kaggle for beginners: how competitions, leaderboards and the progression tiers work, a realistic first month, the workflow strong competitors follow, and a simulation showing why a public leaderboard can rank a worse model higher, so you learn which score gaps to trust before chasing your first medal.
Self-Service Analytics: Empowering Business Teams
How to make self-service analytics work: the three ways organisations divide ownership of data and reports, why managed self-service is the usual goal, the foundations it needs, from certified data to shared metric definitions, warning signs of report sprawl, how to measure success, and how the analyst's role changes.
Real-Time Analytics: Architecture and Tools
How real-time analytics systems are built: the four layers of ingestion, stream processing, serving and consumption, the tools at each layer including Kafka, Spark, Flink and real-time OLAP databases such as Druid, Pinot and ClickHouse, latency budgets, common architectures, and the pitfalls that raise costs.