Description
Network Analytics and Visualization in Python. This course provides a comprehensive guide to understanding and applying graph analysis and network visualization techniques using the Python programming language. The course begins with the basics and guides learners through step-by-step instructions to advanced applications of network analytics. It is designed for data scientists looking to expand their expertise, as well as for technology enthusiasts looking to gain hands-on experience. Network analytics is a powerful skill that has wide applications in a variety of fields, including data science, social sciences, urban planning, and biology. By providing a balance of theoretical foundations and practical skills, this course helps participants analyze and understand complex systems using network-based approaches. Learners will master the Python network science ecosystem, including libraries such as NetworkX and visualization tools, and gain a competitive advantage by expanding their analytical skills in network-based data science. The training process ranges from creating simple graphs to performing advanced analysis, covering both fundamental concepts and practical skills, with a focus on hands-on exercises and real-world examples. By the end of this course, participants will be equipped with the tools, knowledge, and confidence to work with real-world network data and be able to transform complex relationships in data into valuable and understandable insights.
What you will learn
- Building and analyzing networks in Python:
- Create, manipulate, and analyze real-world networks using Python.
- Mastery of the main network metrics and algorithms:
- Applying centrality, modularity, clustering, and other graph-based techniques to identify and describe graph features.
- Developing practical visualization and analysis skills:
- Use Python to create interactive and informative network visualizations for data-driven decision making.
- Network analysis pipeline design:
- Learn the complete network analysis workflow.
- Fundamentals of Network Analysis:
- Includes graph creation and visualization in Python.
- Key Network Concepts:
- Such as centrality, modularity, and network statistics.
- Step-by-step techniques for constructing and analyzing graphs using Python (mainly NetworkX).
- How to combine Python with Gephi for advanced visualization and exploration.
This course is suitable for people who:
- Data scientists and engineers:
- Professionals looking to expand their analytical toolbox with Python-based network and graph analysis approaches.
- Researchers and analysts:
- Academics, social scientists, and business analysts seeking to apply network science techniques to understand complex systems and relationships.
- Software developers:
- People interested in integrating graph-based algorithms and network structures into their applications, from recommender systems to social network analysis.
- Python enthusiasts and learners:
- People with a basic understanding of Python who are eager to enter the world of network analysis and visualization.
Course details
- Publisher: Udemy
- Instructor: Milan Janosov
- Training level: Beginner to advanced
- Training duration: 2 hours and 59 minutes
- Number of lessons: 1
Course headings
Prerequisites for the Network Analytics and Visualization in Python course
- Functional, beginner level Python programming
- Basic knowledge of network science concepts
Course images
Sample course video
Installation Guide
After Extract, view with your favorite player.
Subtitles: None
Quality: 720p
Download link
Downloadly
Rapidgator link
File(s) password: www.downloadly.ir
File size
1.5 GB
