Udemy - Knowledge Graph Engineering with Python

Category : Other
Type: Tutorials
Language: English
Total Size: 2.5 GB
Uploaded By: freecoursewb
Downloads: 38210
Last checked: Aug. 8th '26
Date uploaded: Aug. 8th '26
Seeders: 14814
Leechers: 11282
MAGNET DOWNLOAD
INFO HASH: F8372E6C6BE154C1ACC89980AA8A3B9251BA4412

About Udemy - Knowledge Graph Engineering with Python

Overview

Knowledge Graph Engineering with Python https://WebToolTip.com Published 7/2026 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 3h 7m | Size: 2.48 GB Ontology based Knowledge Graph Assistant: Healthcare domain What you'll learn Build production-ready healthcare knowledge graph applications using Python, Neo4j, and enterprise knowledge graph engineering best practices. Validate and maintain healthcare knowledge graphs using SHACL while ensuring data quality

Frequently Asked Questions

How do I download Udemy - Knowledge Graph Engineering with Python?

Click the magnet or torrent download button on this page to start downloading Udemy - Knowledge Graph Engineering with Python. A BitTorrent client is required.

What is the file size of Udemy - Knowledge Graph Engineering with Python?

The total size of Udemy - Knowledge Graph Engineering with Python is 2.5 GB.

How many seeders are available for Udemy - Knowledge Graph Engineering with Python?

Udemy - Knowledge Graph Engineering with Python currently has 14814 seeders, which affects download speed.

What category is Udemy - Knowledge Graph Engineering with Python in?

Udemy - Knowledge Graph Engineering with Python is listed under Other on 1337x.

Knowledge Graph Engineering with Python

https://WebToolTip.com

Published 7/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 3h 7m | Size: 2.48 GB

Ontology based Knowledge Graph Assistant: Healthcare domain

What you'll learn
Build production-ready healthcare knowledge graph applications using Python, Neo4j, and enterprise knowledge graph engineering best practices.
Validate and maintain healthcare knowledge graphs using SHACL while ensuring data quality, semantic consistency, and integrity.
Develop REST APIs and backend services to query, manage, and integrate healthcare knowledge graphs with enterprise applications.
Design scalable semantic applications by combining healthcare ontologies, graph databases, semantic reasoning, and graph-based analytics.

Requirements
A basic understanding of RDF, OWL, SPARQL, and ontology engineering concepts. Completion of Part 1 is recommended but not mandatory.
Basic knowledge of Python programming, including variables, functions, and working with libraries.
Familiarity with graph databases or a willingness to learn Neo4j and Cypher during the course.
A computer running Windows, macOS, or Linux with permission to install free software such as Python, Neo4j Desktop, Docker (optional), and Visual Studio Code.
No prior experience with SHACL, enterprise knowledge graphs, or semantic application development is required. These concepts are taught step by step throughout the course.