B.Sc. (Data Science) Data Mining Syllabus - Mumbai University
This is the SY BSc Data Science syllabus under NEP 2020, in force from the academic year 2025-26. The University still sets the earlier Choice Based papers alongside it for ATKT candidates, so check which scheme your exam form names before you revise.
Loading syllabus...
Syllabus for Data Mining
Module I: Evolution of Database system, What is data mining? Different data
- repositories, data mining vs knowledge discovery in database, data mining issues, Social implication of data mining, Information Retrieval, Decision support System, Dimensional modelling Data preprocessing Data Preprocessing: Descriptive Data Summarization, Data Cleaning, Data Integration and Transformation, Data Reduction, Data Discretization and Concept Hierarchy Generation.
- Mining Frequent Patterns, Associations, and Correlations: Basic Concepts, Efficient and Scalable Frequent Itemset Mining Methods, Mining Various Kinds of Association Rules, From Association Mining to Correlation Analysis, Constraint-Based Association Mining
Module II: Classification and Prediction: What Is Classification?, What Is
- Prediction?, Classification by Decision Tree Induction, Bayesian Classification, Rule-Based Classification, Classification by Back- propagation Associative Classification, Classification by Association Rule Analysis Cluster Analysis: What Is Cluster Analysis?, Types of Data in Cluster Analysis, Partitioning Methods, Hierarchical Methods, Density-Based Methods, Grid-Based Methods, Model-Based Clustering Methods, Clustering High-Dimensional Graph Mining, Social Network Analysis, and Multirelational Data Mining: Introduction to Graph Mining, Social Network Analysis, Multi- relational Data Mining. Mining Object, Spatial, Multimedia, Text, and Web Data: Multidimensional Analysis and Descriptive Mining of Complex Data Objects, Spatial Data Mining, Multimedia Data Mining, Text Mining, Mining the world wide web.
Textbooks
- 1 M. H. Dunham, “Data Mining: Introductory and Advanced Topics”, Pearson Education.
- 2 J. Han and M. Kamber, “Data Mining: Concepts and Techniques”, Second Edition, Elsevier.
- 1 Krzysztof J, Cios,W. Pedrycz, R, W.Swiniarski, L.A. Kurgan, “Data Mining” A Knowledge Discovery Approach”, Springer (Unit I).
- 2 Dr. CarolynK. Hamm, “Oracle Data Mining”, RampantTechPress, SPD.
- 3 C. Ballard, Dynamic Warehousing and Data Mining Made Easy, ReddBooks, IBM (SPD)
- 4 H.Witten and E. Frank. Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann. 2005.
- 5 D. Hand, H. Mannila and P. Smyth. Principles of Data Mining. Prentice-Hall. 2001.
- 6 Z.Tang and J MacLennan, “Data Mining with SQL Server 2005”,Wiley
Reproduced from the University of Mumbai syllabus for B.Sc. (Data Science) under NEP 2020, in force from the academic year 2025-26. 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.