Learn how to frame a problem from the standpoint of networks and relationships
Calculate various measurements of networks and understand underlying network structure
Identify weak points and key connectors in networks and supply chains
Syllabus: Introduction to Network Analysis
This course is designed for students who are comfortable with R and have experience with data analysis and data manipulation. In just 100 minutes of instructional time, students learn how to think about networks, quantify and analyze network relationships, and identify key nodes in a network.
By the end of this course, students will be able to:
Frame a problem from the standpoint of networks and relationships.
Calculate and analyze various network measurements to understand the underlying structure.
Identify potential weak points and key players to prevent failures or leverage the network.
- Concept reviews: these are comprised of short five question quizzes that cover the most important concepts and ideas in each lesson. They encourage holistic understanding and are multi-faceted ques=on types (i.e. drag and drop, fill-in-the-blanks, matching, etc).
- Exercises: these are additional videos that cover the coding functions in the instructional video in more depth. They are project-based and include coding templates for students to strengthen their skills outside of the course.
- Accompanying PDFs to use as reference materials
- R code templates from the instructional videos and exercises
- Data sets used in the instructional videos and exercises
1. An overview of networks (21 min)
What’s new with networks?
Networks in business
The impact of networks
2. Setting up your network data (24 min)
Geocoding network data
How do you measure a network?
Wrangling network data
3. Analyzing your network structure (28 min)
Visualizing your network
Identifying key network hubs
Summarizing network metrics
4. Analyzing your network strength (25 min)
Testing network resiliency
Building a function for networks
Identifying disconnected networks
Total instruction time: 1 hr, 38 min
Merav Yuravlivker is a nationally ranked instructor and co-founder of Data Society. She used data-driven strategies in the classroom to maximize educational outcomes and has over 10 years of experience in instructional design, training, and teaching. Merav has helped bring new insights to businesses and move their organizations forward through implementing data analytics strategies.
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