Mastering Databases with Python SQL, NoSQL, Vector DBs

Free download скачать Mastering Databases with Python SQL, NoSQL, Vector DBs
Published 8/2026
Created by Ayoub Allali
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: Arabic | Duration: 44 Lectures ( 8h 52m ) | Size: 6.7 GB

Mastering Databases with Python: SQL, NoSQL, Vector DBs
[h2]What you'll learn[/h2]
⚡ Design and query relational databases using core SQL concepts including DDL, DML, DCL, TCL, joins, grouping, and sorting.
⚡ Build applications with NoSQL databases, including MongoDB (document), Redis (key-value), Neo4j (graph), and Cassandra (column-family).
⚡ Connect and perform CRUD operations across SQL and NoSQL systems natively using Python drivers and frameworks.
⚡ Store and query vector embeddings using FAISS and ChromaDB to build Retrieval-Augmented Generation (RAG) AI applications in Python.
[h2]Requirements[/h2]
❗ Basic knowledge of Python programming
[h2]Description[/h2]
Master modern data storage architectures and learn how to manage, query, and integrate databases using Python. This course provides a complete end-to-end journey from foundational relational models to cutting-edge AI vector search systems.
Whether you are a developer, data scientist, or AI engineer, understanding how to select, structure, and query the right database is crucial for building scalable, high-performance applications.
[h2]What You Will Learn[/h2]
✨Relational Databases & SQL: Core principles of relational modeling, execution of complex DDL, DML, DCL, and TCL queries, grouping, sorting, and join operations.
✨NoSQL Paradigm: Key concepts, CAP Theorem, and practical implementation across document stores (MongoDB), key-value databases (Redis), and graph structures (Neo4j).
✨Python Database Frameworks: Native Python drivers and ORMs for seamlessly connecting Python applications to MySQL, MongoDB, Firebase, Redis, Apache Cassandra, and Neo4j.
✨Vector Databases for AI: Foundations of embeddings, vectoring frameworks, FAISS distance metrics, and ChromaDB integration for AI applications.
✨Retrieval-Augmented Generation (RAG): Hands-on implementation of RAG pipelines using modern AI architecture and NVIDIA Nemotron.
✨Specialized Data Systems: Industrial-grade time-series and IoT data handling with Apache IoTDB.
Every section combines practical concepts with real-world Python implementations. By the end of this course, you will have the skills needed to design, query, and integrate diverse database systems into modern software and AI workflows.
[h2]Who this course is for[/h2]
⭐ Aspiring Database Administrators (DBAs), Data Engineers, and Database Managers.
⭐ Data Scientists and AI Engineers seeking to build Retrieval-Augmented Generation (RAG) pipelines using Vector DBs like FAISS and ChromaDB.
[h2]Homepage[/h2]

Код:

https://www.udemy.com/course/mastering-databases-with-python-sql-nosql-vector-dbs

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Mastering Databases with Python SQL, NoSQL, Vector DBs

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Поделиться12026-08-25 15:01:51

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