Link to Content:

DataCamp Network Analysis in Python Part 2

Created/Published/Taught by:

DataCamp

Eric Ma

Hugo Bowne-Anderson

Yashas Roy

Content Found Via:

DataCamp

Free? Partially: Some Free Content, Some Paid

Cost Range:

$0.00 - $29.00

Tags: bipartite graphs / graph projections / network analysis / network analytics / python / recommender systems

Difficulty Rating:

From DataCamp:

“Have you taken DataCamp’s Network Analysis in Python (Part 1) course and are yearning to learn more sophisticated techniques to analyze your networks, whether they be social, transportation, or biological? Then this is the course for you! Herein, you’ll build on your knowledge and skills to tackle more advanced problems in network analytics! You’ll gain the conceptual and practical skills to analyze evolving time series of networks, learn about bipartite graphs, and how to use bipartite graphs in product recommendation systems. You’ll also learn about graph projections, why they’re so useful in Data Science, and figure out the best ways to store and load graph data from files. You’ll consolidate all of this knowledge in a final chapter case study, in which you’ll analyze a forum dataset and come out of this course a Pythonista Network Analyst ninja!”

This course consists of four chapters:

- Bipartite graphs & product recommendation systems
- Graph projections
- Comparing graphs & time-dynamic graphs
- Tying it up!

Recommended Prerequisites: Network Analysis in Python (Part 1)

Go to Content: DataCamp – Network Analysis in Python (Part 2)

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