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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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Building REST APIs with Python: A Practical Guide
The design decisions behind a REST API that other programs can depend on: resource URLs, what GET, POST, PUT and DELETE promise, the status codes that matter, validation at the boundary, one error format, and pagination. Shown with a small Flask API exercised through its test client.
Building a CLI Tool in Python with argparse
A step-by-step build of a small command-line tool with Python's argparse: positional arguments and typed options, choices and flags, subcommands, what happens on bad input, how to test the parser, and how to install the tool as a command with pyproject.toml.
Building an End-to-End MLOps Pipeline
An end-to-end MLOps pipeline joins data validation, versioning, tracking, a registry, serving, monitoring and retraining into one loop. This guide runs that loop on real motorway traffic data: monitoring caught a summer surge, one retrained challenger was rejected, a second was promoted, and 2018 error fell 13%.
Building a Metadata Framework for ADF Pipelines
A control table and a ForEach copy many tables. A framework is what makes that safe to operate: configuration you can validate, a log of every load, stages that run in order, and reruns that resume instead of repeating. This guide designs each part for Azure Data Factory, with the restart logic shown working.
Building a Sales Dashboard: A Hands-On Project
A hands-on sales dashboard project built on a real online retailer's 541,909 transaction lines: agreeing the questions and KPIs, removing cancellations, postage and fees, computing monthly revenue, orders and average order value, finding the breakdowns that matter, and laying it out so key numbers are read first.
Building a Sales Dashboard in Power BI from Scratch
A Power BI sales dashboard built from scratch on the Chinook sample database: a star schema and date table, core DAX measures for revenue, orders, customers, order value and year-over-year change, the exact values each should return, a sales rep comparison that ranks differently by total and per customer, and a layout.