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B.E Artificial Intelligence and Machine Learning Big Data Analytics Lab 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.

Big-Data-Analytics-Lab.pdf
Semester 7 · Fourth Year AI-ML · 1 credit · 50 marks

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Syllabus for Big Data Analytics Lab

Semester 7 · Fourth Year AI-ML · 1 credit · 50 marks

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.

  • 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. To install and configure MongoDB/ Cassandra/ HBase/ Hypertable to execute NoSQL commands. Experiment on Hadoop Map-Reduce / PySpark: -Implementing simple algorithms in Map-Reduce: Matrix multiplication, Aggregates, Joins, Sorting, Searching, etc. Create HIVE Database and Descriptive analytics-basic statistics, visualization using Hive/PIG/R. Write a program to implement word count programs using MapReduce. Implementing DGIM algorithm using any Programming Language/ Implement Bloom Filter using any programming language. Implementing any one Clustering algorithm (K-Means/CURE) using Map-Reduce. Streaming data analysis – use flume for data capture, HIVE/PYSpark for analysis of twitter data, chat data, weblog analysis etc. Implement PageRank using Map-Reduce. 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 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.

PDF 7.8 (R-A) B.E. (Artificial Intelligence and Machine Learning) Sem I & II (Revised, NEP 2020) NEP 2020 syllabus Read full PDF Read
PDF 6.21 (N) B.E. (Artificial Intelligence and Machine Learning) Sem III & IV (NEP 2020) NEP 2020 syllabus Read full PDF Read
PDF 6.42 (R) B.E. (Artificial Intelligence and Machine Learning) Third Year, Sem V & VI (REV-2019 'C' Scheme) REV-2019 'C' Scheme syllabus Read full PDF Read
PDF B.E. (Artificial Intelligence and Machine Learning) Fourth Year, Sem VII & VIII (REV-2019 'C' Scheme) REV-2019 'C' Scheme syllabus Read full PDF Read
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