Graph Analytics Literacy (Beginner Level)

Topics covered

• compare and contrast graph databases and relational data structures
• compute the shortest path in a weighted graph using greedy traversal and the distance table
• describe the structure and components of a graph
• list the different types of graphs and explore their structure
• model graphs using an adjacency list and adjacency set and compare the two representations
• model graphs using a square adjacency matrix to represent nodes and edges
• perform common graph operations to compute adjacent nodes, degree of a node, and check edge connections on undirected graphs
• recall how depth-first and breadth-first traversal works
• recall the properties of greedy algorithms
• represent graphs using an adjacency matrix in Python
• represent graphs using an adjacency set in Python
• use graph nodes and edges to model entities and relationships in the real world