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Network Analysis and Network Optimization in SAS® Viya®
VYNA : VYNA22
This course provides a set of network analysis and network optimization solutions using the NETWORK and OPTNETWORK procedures in SAS Viya. Real-world applications are emphasized for each algorithm introduced in this course, including using network analysis as a stand-alone unsupervised learning technique, as well as incorporating network analysis and optimization to augment supervised learning techniques to improve machine learning model performance through input/feature creation.
Learn How To
- Structure networks as matrices and in the required data format (or formats) to read network data into the NETWORK and OPTNETWORK procedures.
- Define the fundamental components of network topology, including nodes, links, self-links, link weights, node weights, and directionality to understand the different ways to construct a network.
- Compute and interpret network-level measures, including network density, diameter, and average shortest path.
- Compute and interpret centrality measures, including degree centrality, eigenvector centrality, betweenness centrality, closeness centrality, and PageRank centrality.
- Compute, apply, and interpret subnetwork analyses such as connected components, shortest paths, cycles, cliques, and community detection, among others.
- Perform network querying from graph database network structures using the PATTERNMATCH statement.
- Perform network projection to transform a bipartite network into a single network with real-world applications.
- Apply network optimization algorithms such as the linear assignment problem, the traveling salesman problem, and the minimum spanning tree, among others, to solve real-world problems.
Who Should Attend
Anyone interested in learning to incorporate network analysis and network optimization to provide solutions and solve real-world business challenges, including data scientists, business analysts, statisticians, and other quantitative professionals. Managers, directors, and leaders with a quantitative background are also encouraged to attend to learn how network analysis and optimization can be integrated into a broader portfolio of data science and machine learning applications.
Prerequisites
In order to complete practices with classroom software, attendees should have basic familiarity with statistics and mathematical concepts and be comfortable programming in SAS using DATA steps. Experience using macros is helpful, but not required.
SAS Products Covered
SAS Viya
Course Outline
Concepts in Network Analysis
- Introduction.
- Network-level concepts.
- Adjacency matrices and degree centrality.
- Introduction to the NETWORK procedure.
- Introduction.
- Eigenvector centrality.
- Betweenness and closeness centrality.
- Influence centrality (self-study).
- Hub and authority centrality.
- PageRank centrality.
- Connected and biconnected components.
- Maximal cliques.
- Community detection.
- Paths, shortest paths, and cycles.
- Pattern matching.
- Introduction to bipartite networks.
- Network projection.
- Introduction.
- Linear assignment problem.
- Minimum spanning tree.
- Maximum spanning tree (self-study).
- Traveling salesman problem.
- Minimum cost network flow (self-study).
- Total unduplicated reach and frequency (TURF) analysis.
- Multiple traveling salesman problem (mTSP).
- Minimum cost network flow.
- Introduction.
- Eigenvector centrality using IML.
- Hub and authority centrality using IML.
- PageRank centrality using IML.
Live Class Schedule
Duration: 14 hours
Step into our live classes and experience a dynamic learning environment where you can ask questions, share ideas, and connect with your instructor and classmates. With on-demand lab hours, you can explore the material at your own pace. Our globally acclaimed instructors will motivate you to think bigger, so you can take what you've learned and achieve your biggest goals.
This course isn't publicly scheduled, but private training and mentoring may be available. Contact us to explore options.
Private Training
Get training tailored specifically for your team, led by expert SAS instructors. Choose from virtual sessions, or training at your location (or ours). Perfect for teams seeking a customized curriculum and plenty of interaction with a SAS specialist. We'll schedule it at a time that works for you.
Mentoring Services
Take your training to the next level with personalized mentoring. While private training offers structured coursework, mentoring provides hands-on, real-time support from a subject matter expert. As you work with your own data, you'll receive expert guidance to help you uncover insights, unlock the full potential of your data, and make faster progress. Perfect for those looking to apply what they’ve learned and see quicker results.