M.Sc. (Information Technology) Big Data Analytics Practical Syllabus - Mumbai University
This is the University of Mumbai syllabus for M.Sc. (Information Technology) under NEP 2020, in force from the academic year 2024-25. Semesters I and II are set by item 6.29 (N) and Semesters III and IV by item 6.2 (N). The University examines this programme under form 1113161, whose Summer 2026 timetable is headed NEP-2020; the distance and older Choice Based modes of the same degree are examined under different forms and different papers.
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Syllabus for Big Data Analytics Practical
- I 1 Install, configure and run Hadoop and HDFS ad explore HDFS. 2 Implement word count / frequency programs using MapReduce 3 Implement an MapReduce program that processes a weather dataset. 4 Implement an application that stores big data in Hbase / MongoDB and manipulate it using R / Python 5 Implement the program in practical 4 using Pig. 6 Configure the Hive and implement the application in Hive. 7 Write a program to illustrate the working of Jaql. 8 Implement the following: 9 Implement Decision tree classification techniques
- II 10 Implement SVM classification techniques 11 Solve the following: 12 REGRESSION MODEL Import a data from web storage. Name the dataset and now do Logistic Regression to find out relation between variables that are affecting the admission of a student in an institute based on his or her GRE score, GPA obtained and rank of the student. Also check the model is fit or not. require (foreign), require(MASS). 13 MULTIPLE REGRESSION MODEL Apply multiple regressions, if data have a continuous independent variable. Apply on above dataset. 14 Solve the Following: 15 CLASSIFICATION MODEL a. Install relevant package for classification. b. Choose classifier for classification problem. c. Evaluate the performance of classifier. 16 CLUSTERING MODEL a. Clustering algorithms for unsupervised classification. b. Plot the cluster data using R visualizations. OC 1: Understand the key issues in big data management and its associated applications in intelligent business and scientific computing. OC 2: Acquire fundamental enabling techniques and scalable algorithms like Hadoop, Map Reduce and NO SQL in big data analytics. OC 3: Interpret business models and scientific computing paradigms, and apply software tools for big data analytics. OC 4: Achieve adequate perspectives of big data analytics in various applications like recommender systems, social media applications etc.
Reproduced from the University of Mumbai syllabus for M.Sc. (Information Technology) under NEP 2020, in force from the academic year 2024-25. Wording, unit numbering and lecture allocation are as printed in that syllabus. The PDF above is the syllabus's own page, unaltered.
The complete syllabus
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