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Home / Syllabus / B.E. (Artificial Intelligence and Data Science) / Fourth Year BE AI and DS / Semester 7 / Big Data Analytics Lab

B.E. (Artificial Intelligence and Data Science) Big Data Analytics Lab Syllabus - Mumbai University 2026

This is the Fourth Year BE AI and DS syllabus under CBCS REV-2019 'C' Scheme, in force from the academic year 2023-24. The University has published no NEP 2020 syllabus for Semesters V to VIII of any engineering branch, so this is the scheme you are examined on — exam form 1T01817 and 1T01818. The first and second years of the degree are on NEP 2020.

Big Data Analytics Lab.pdf
Semester 7 · Fourth Year BE AI and DS · 1 credits · CBCS REV-2019 'C' Scheme

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Syllabus for Big Data Analytics Lab

Semester 7 · Fourth Year BE AI and DS · 1 credits · CBCS REV-2019 'C' Scheme

Module 1

  • Hadoop HDFS Practical: -HDFS Basics, Hadoop Ecosystem Tools Overview. -Installing Hadoop. -Copying File to Hadoop. -Copy from Hadoop File system and deleting file. -Moving and displaying files in HDFS. -Programming exercises on Hadoop.

Module 2

  • Use of Sqoop tool to transfer data between Hadoop and relational database servers. a. Sqoop - Installation. b. To execute basic commands of Hadoop eco system component Sqoop.

Module 3

  • To install and configure MongoDB/ Cassandra/ HBase/ Hypertable to execute NoSQL commands.

Module 4

  • Experiment on Hadoop Map-Reduce / PySpark: -Implementing simple algorithms in Map-Reduce: Matrix multiplication, Aggregates, Joins, Sorting, Searching, etc.

Module 5

  • Create HIVE Database and Descriptive analytics-basic statistics, visualization using Hive/PIG/R.

Module 6

  • Write a program to implement word count programs using MapReduce.

Module 7

  • Implementing DGIM algorithm using any Programming Language/ Implement Bloom Filter using any programming language.

Module 8

  • Implementing any one Clustering algorithm (K-Means/CURE) using Map-Reduce.

Module 9

  • Streaming data analysis – use flume for data capture, HIVE/PYSpark for analysis of twitter data, chat data, weblog analysis etc.

Module 10

  • Implement PageRank using Map-Reduce.

Module 11

  • Implement predictive Analytics techniques (regression / time series, etc.) using R/ Scilab/ Tableau/ Rapid miner.

Useful Links

  • 1 https://nptel.ac.in/courses/117/102/117102062/
  • 2 https://epgp.inflibnet.ac.in/Home/ViewSubject?catid=305
  • 3 https://nptel.ac.in/courses/106/106/106106167/

Reproduced from the University of Mumbai syllabus for B.E. (Artificial Intelligence and Data Science), item 6.12 (N), under CBCS REV-2019 'C' Scheme, in force from the academic year 2023-24. Wording, module numbering and hours are as printed in that syllabus.

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.

PDF B.E. Artificial Intelligence and Data Science - First Year, Semester I and II - NEP 2020 - Item 7.7 (R-A) NEP 2020, Semesters I and II, in force from 2024-25 Read full PDF Read
PDF B.E. Artificial Intelligence and Data Science - Second Year, Semester III and IV - NEP 2020 - Item 6.20 (N) NEP 2020, Semesters III and IV, in force from 2025-26 Read full PDF Read
PDF B.E. Artificial Intelligence and Data Science - Third Year, Semester V and VI - CBCS REV-2019 C Scheme - Item 6.42 (R) CBCS REV-2019 'C' Scheme, Semesters V and VI, in force from 2022-23 Read full PDF Read
PDF B.E. Artificial Intelligence and Data Science - Fourth Year, Semester VII and VIII - CBCS REV-2019 C Scheme - Item 6.12 (N) CBCS REV-2019 'C' Scheme, Semesters VII and VIII, in force from 2023-24 Read full PDF Read
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