This Network Analysis and Network Optimization in SAS Viya training course provides a set of network analysis (graph theory) 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.
By attending Network Analysis and Network Optimization in SAS Viya workshop, delegates will learn 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
- Familiarity with statistics and mathematical concepts and be comfortable programming in SAS using DATA steps.
- Experience using macros is helpful, but not required.
The Network Analysis and Network Optimization in SAS Viya class is ideal for:
- 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.