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Graph Analysis & Social Networks Learning Guide.pdf

GA_10BA_103000903_2S_2022-23.pdf

Preview of Graph Analysis & Social Networks Learning Guide

🔗 Source: upm.es

📊 Size: 300 KB

📄 Pages: 10 pages

⬇️ Downloads: 225

Summary

- Subject: Graph Analysis And Social Networks (103000903)
- Degree Programme: Master Universitario En Ciencia De Datos (10BA)
- Academic Year & Semester: 2022/23 - Semester 2
- Credits: 3 ECTS
- Faculty:
- Emilio Serrano Fernández ([email protected])
- Javier Bajo Pérez (Subject Coordinator, [email protected])
- Skills & Learning Outcomes:
- Apply techniques for data visualization and analysis
- Use advanced methods to solve complex problems
- Understand and create complex information systems
- Debate scientific knowledge and research bases
- Apply AI techniques in real-world data scenarios
- Understand the fundamentals of analytical visualization techniques
- Course Description: Focuses on graph and network analysis in the context of social computing, covering topics such as graph mining, sentiment analysis, trust, and reputation in social networks.
- Syllabus:
1. Introduction to Social Computing
2. Graph mining and Social Network Analysis
3. Sentiment Analysis in Social Networks
4. Trust and reputation in social networks
5. Practical assignment

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Description

This learning guide outlines the coordination process of learning activities for the subject "Graph Analysis And Social Networks" in the Master Universitario En Ciencia De Datos program.

Technical Information

File Format: PDF
File Size: 300 KB
Pages: 10
Language: EN
Total Downloads: 225
Last Updated: 6 days ago

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This PDF document about Graph Analysis & Social Networks Learning Guide provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into Graph Analysis & Social Networks Learning Guide.