Have a look at our take on Best Data Science with R Courses.
After finishing the course, you will be able to analyze any network with basic centrality and similarity measures and create beautiful and interactive network visualizations. The course will provide you with additional video lectures, quizzes, assignments, rich learning content, and much more to help you learn the subject more clearly.
In this course, you will acquire a clear demonstration of network analysis with several R packages, including dplyr, igraph, ggplot2, and visNetwork. If you want to know more about social networks, information networks, and the neural networks of our brains, then this network science course can help you learn a lot of things. Network Analysis in the Tidyverse (DataCamp) Review: I’ve used other sites, but DataCamp’s been the one that I’ve stuck with. – Explore the partitioning of networks into sub-networks and determine which vertices are highly related to one another than others
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– Learn how to identify special relationships between vertices with the help of metrics like assortativity, and how to create interactive network plots using threejs – Included with four different chapters, each of which will guide you to different concepts of social networks, such as identifying essential vertices, special relationships, etc. – Get introduced to the fundamental concepts of social network analysis while learning how to use the igraph R package for exploring and analyzing social network data The course is covered with multiple video lectures, quizzes, graded assignments, and much more to help you better equipped with the course content. During the course, you will cover a variety of network structures, such as cliques, triangles, etc. Taking this course will help you learn how to plot networks and their attributes, how to identify important vertices with measures like degree and betweenness, and much more. If you want to learn how to visualize and work with network data, and how to use igraph package for creating networks from edgelists and adjacency matrices, then this is the right course for you. Review: DataCamp is the top resource I recommend for learning data science. – Get access to multiple assignments, graded quizzes, video lectures, rich-learning content, and much more to improve your learning skills – Learn different ways of identifying nodes that are essential in a network, as well as learn the basics of path-finding algorithms – Know about NetworkX library that allows users to manipulate, analyze, and model graph data while learning about the diverse types of graphs and how to visualize them rationally – Get introduced to the fundamental concepts in network analytics while going through a real-world Twitter network dataset Check out our compilation of Best Neural Network Courses. Also, after course completion, you will get a certificate of completion. During the course, if you face any queries or issues with the course content, then the instructor will help you resolve it. The course is designed by Eric Ma, who works at MIT in solving big biological data problems.
You will study how to smear the concepts to real-world network data with the powerful NetworkX library, and how to develop your network thinking skills and be able to look at your data with a fresh perspective. This is a beginner level course that will equip you with all the skills required for analyzing, visualizing, and making sense of networks. Introduction to Network Analysis in Python (DataCamp)
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