B.E Artificial Intelligence and Machine Learning Graph Data Science 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
1
- 2 3 4 5 6
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. Module numbering is as printed there too.
The complete syllabus
This subject is cut from the University circular for its year. Open a document here if you want the whole thing rather than a single subject.