B.E Artificial Intelligence and Machine Learning Graph Data Science Lab Syllabus - Mumbai University
This is the Fourth Year AI-ML syllabus under REV-2019 'C' Scheme, in force from the academic year 2023-24. The University has not yet published an NEP 2020 syllabus for this year of the degree, and this is the scheme its examinations are set on.
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Syllabus for Graph Data Science Lab
Suggested List of Experiments
- 1 Graph Database Fundamentals: ○ Install and set up a graph database system (e.g., Neo4j) on a local machine. ○ Familiarize yourself with the graph database environment, including the query language (Cypher) and browser interface.
- 2 Data Modeling with Graphs: ○ Design a data model using the labeled property graph model for a specific domain (e.g., social network, e-commerce). ○ Implement the data model in the graph database and populate it with sample data. 3, Basic Graph Queries: ○ Perform basic graph queries using Cypher to retrieve nodes, relationships, and their properties. ○ Explore different query patterns, such as finding paths, filtering nodes, and ordering results.
- 4 Advanced Graph Queries: ○ Extend your query knowledge by performing more complex graph queries, including subgraph matching, aggregation, and conditional filtering. ○ Optimize query performance by understanding and utilizing indexes.
- 5 Graph Database Administration: ○ Learn and practice essential administrative tasks, such as managing users, roles, and access control. ○ Perform backup and restore operations to ensure data integrity.
- 6 Importing and Exporting Data: ○ Import data from external sources (e.g., CSV files) into the graph database. ○ Export graph data to different formats for analysis or sharing.
- 7 Graph Algorithms and Analytics: ○ Explore the built-in graph algorithms provided by the graph database system (e.g., centrality, community detection). ○ Apply graph algorithms to analyze and extract insights from your graph data
- 8 Graph Visualization and Exploration: ○ Utilize visualization tools and libraries to visualize your graph data. ○ Explore and navigate the graph visually to gain a better understanding of its structure and relationships.
- 9 Performance Optimization: ○ Identify and address performance bottlenecks in your graph database application. ○ Optimize queries, indexes, and data modeling to improve overall system performance.
- 10 Scaling and Replication: ○ Learn techniques for scaling and replicating a graph database to handle larger datasets and higher workloads. ○ Implement and test replication strategies to ensure data availability and fault tolerance. *11. Real-World Use Cases: ○ Choose a specific real-world use case (e.g., recommendation systems, fraud detection) and apply graph database techniques to solve the problem. ○ Design and implement a graph database application that addresses the unique requirements of the chosen use case.
Textbooks
- 1 Introduction to Graph Theory Fourth edition, Robin J. Wilson
- 2 Daphne Koller and Nir Friedman, "Probabilistic Graphical Models: Principles and Techniques”, Cambridge, MA: The MIT Press, 2009 (ISBN 978-0-262-0139- 2).
- 3 Graph databases, Ian Robinson, Jim Webber & Emil Eifrem 1 "Graph Databases: New Opportunities for Connected Data" by Ian Robinson, Jim Webber, and Emil Eifrém.
- 2 "Neo4j in Action" by Aleksa Vukotic, Nicki Watt, and Tareq Abedrabbo.
- 3 "Graph Databases for Beginners" by Mark Needham and Amy E. Hodler.
- 4 "Practical Neo4j" by Gregory Jordan.
- 5 "Learning Neo4j" by Rik Van Bruggen.
- 6 "Graph Database Applications and Concepts with Neo4j" by Dionysios Synodinos. Digital References:
- 1 https://web4.ensiie.fr/~stefania.dumbrava/OReilly_Graph_Databases.pdf
- 2 https://www.quackit.com/neo4j/tutorial/
Reproduced from the University of Mumbai syllabus for B.E. (Artificial Intelligence and Machine Learning) under REV-2019 'C' Scheme, in force from the academic year 2023-24. Wording is as printed in that syllabus. The University sets no module list for this course; what she publishes is the objectives, outcomes and assessment guidelines reproduced above.
The complete syllabus
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