I have an exam for the following subject : Network & Graph Analytics

Can you please suggest me how to prepare for the subject . I have class slides but I want to know if there are more resources from which I can practice.
Pls suggest a methodology too.
The exam will consist of MCQs and Descriptive Answers.
Syllabus :
Session 1: Thinking Graph

• Introduction to Graphs
• Path Analysis
• Connectivity Analysis
• Community Analysis
• Centrality Analysis
• Pattern Matching
• Programming Model for Graphs
• Applications of Graph and introduction to Graph tools and representations
  
  Session 2:  Semantic Web Technologies
• Evolution of Semantic Web: Web 1.0-Web 2.0-Semantic Web
• Graph Data & Databases
• Ontology: RDF, RDFS, OWL
• Semantic Modeling
• Querying Semantic Data: SPARQL

 

Session 3: Enterprise Knowledge Graphs

• Context of Enterprise Knowledge Graphs,
• Knowledge Layer
• Enterprise Vocabularies
• Representing Knowledge in Graph
• Inferencing & Reasoning
• Context based & personalized Intelligent Insights
• Data Provenance & Data Virtualization

Session 4: Advanced EKG: Knowledge Graph Extraction from Unstructured Data  & AI

• Evaluating Unstructured text for extracting Knowledge Graphs
• Knowledge Graph embeddings: Entity Extraction, Relationship Extraction, Coreference, Disambiguation, Semantic  Role Labeling, Knowledge Discovery
• Frameworks in the Market and comparison
• Knowledge Graph Architecture
• AI & Generative AI Context and Usage of Knowledge Graphs
• Inferencing based Context and Prompt Engineering
• Advanced Embeddings driven Content Generation
• Explainable AI with Knowledge Graphs
• Advanced Knowledge Catalogs for Enterprise Data using EKG

Session 5: Implementing Enterprise Knowledge Graphs

• Use cases
• Enterprise Data Fabric
• Digital Twins
• Fraud Analytics
• Healthcare Usecase
• Path Forward and Areas in Research