Data Science Tutorials

Learn what causes circular imports in Python, how they break your code, and explore proven strategies to detect, fix, and prevent them in real projects.

Use this method to make better predictions from real-world data. Learn how to minimize errors and find the most reliable trend line.

Learn how to set up and run Mistral's Magistral Small model using Ollama and vLLM, and build a demo project that debugs faulty logic.

Learn how to set up Apache Kafka with Docker using Compose. Discover best practices, common pitfalls, and tips for development and testing environment

Understand how the t-distribution helps when sample sizes are small or population variance is unknown. Compare it to the normal and Z-distributions to learn when each is appropriate.

Learn how to use PI() in Excel so you have precision with mathematical formulas. Discover examples, syntax details, and tips for harnessing π in calculations.

Master the `SEQUENCE()` function to supercharge your spreadsheet skills. Learn how to create dynamic lists, automate calculations, and unlock new Excel possibilities.

Discover how Microsoft’s fully managed, multi-model database delivers low-latency performance, elastic scalability, and real-time capabilities for AI, IoT, e-commerce, and more.

Understand how Amazon Neptune handles highly connected data using graph models like property graphs and RDF. Discover how to write queries in Gremlin, openCypher, and SPARQL for real-world tasks like fraud detection and recommendations.

A step-by-step tutorial on building, testing, deploying, and integrating a Gradio MCP server with Tavily, Hugging Face Spaces, Cursor AI and Claude Desktop.

Learn how to read CSV files efficiently in PySpark. Explore options, schema handling, compression, partitioning, and best practices for big data success.

Learn efficient PySpark filtering techniques with examples. Boost performance using predicate pushdown, partition pruning, and advanced filter functions.