Data Science Tutorials

Master Python's f-strings, the most elegant way to handle string formatting in your code. This guide covers everything from basic syntax to advanced techniques. Learn how to write cleaner, more maintainable code with real-world examples.

Learn to build effective command-line interfaces in Python using the argparse module. This guide walks you through basic and advanced features, with practical examples and tips to improve your programming skills.

Learn how Anthropic's contextual retrieval improves the accuracy of retrieval systems and how to implement it step-by-step.

Learn how to set up the AWS Multi-Agent Orchestrator framework and build a demo project focused on multi-agent orchestration.

Learn how to validate your data with Great Expectations in Python with this end-to-end tutorial!

Learn how to use Microsoft’s TinyTroupe to simulate interactions between AI personas with distinct characteristics for different purposes.

Learn how to use Mistral’s Pixtral Large via Le Chat or access it programmatically through the API on La Plateforme.

This tutorial teaches you how to use Docker to build and deploy a document Q&A application on the Hugging Face Cloud.

Learn the art of pivoting rows into columns in SQL in Oracle, MySQL, and SQL Server. Explore practical methods with detailed examples to boost your data engineering skills.

Discover how the harmonic mean handles rates and ratios in data science and finance. Learn its calculation methods and when to use it for more accurate analysis.

.loc selects data using row and column names (labels), while .iloc uses numerical indices (positions). Learn how to use both with examples.

Learn how to implement late chunking with Jina AI to improve context preservation and retrieval accuracy in RAG applications.