B.E Artificial Intelligence and Machine Learning Data Warehousing and Mining Lab Syllabus - Mumbai University
This is the Third Year AI-ML syllabus under REV-2019 'C' Scheme, in force from the academic year 2022-23. 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 Data warehousing and Mining Lab
Module 1: Data Warehouse Construction a) Real life Problem to be defined for Warehouse Design
- b) Construction of star schema and snow flake schema c) ETL Operations.
Module 2: Construction of Cubes , OLAP Operations, OLAP Queries
Module 3: Tutorials a) Solving exercises in Data Exploration b) Solving exercises in Data preprocessing
Module 4: Using open source tools Implement Classifiers
Module 5: Using open source tools Implement Association Mining Algorithms
Module 6: Using open source tools Implement Clustering Algorithms
Module 7: Implementation of any one classifier using languages like JAVA/ python
Module 8: Implementation of any one clustering algorithm using languages like JAVA/ python
Module 9: Implementation of any one association mining algorithm using languages like JAVA/ python .
Module 10: Implementation of page rank algorithm.
Module 11: Implementation of HITS algorithm.
Useful Links
- 1 www.leetcode.com
- 2 www.hackerrank.com
- 3 www.cs.usfca.edu/~galles/visualization/Algorithms.html
- 4 www.codechef.com
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 2022-23. 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.