Guidelines:
Course Objectives:
1. To provide an overview of
an exciting growing field of Big Data analytics.
2. To discuss the challenges traditional
data mining algorithms face when analyzing
Big Data.
3. To introduce the tools required
to manage and analyze
big data like Hadoop, NoSql
MapReduce.
4. To teach the fundamental techniques and
principles in achieving big
data analytics with
scalability and streaming capability.
5. To introduce to the student's several
types of big data like social
media, web graphs and data streams.
6. To enable students to have skills that
will help them to
solve complex real-world problems for decision support.
Course Outcome :
1. Explain
the motivation for big data systems and identify the main sources of
Big Data in the real world.
2. Demonstrate
an ability to use frameworks
like Hadoop, NoSQL to
efficiently store retrieve and process Big Data for Analytics.
3. Implement
several Data-Intensive tasks using the Map-Reduce Paradigm
4. Apply
several newer algorithms for Clustering Classifying and finding associations in
Big Data
5. Design algorithms to
analyze
Big data like streams, Web Graphs and Social Media data.
6. Design and implement successful
Recommendation engines for enterprises.
- Teacher: Sunantha Krishnan
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- Teacher: Uday Nayak
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- Teacher: Aruna Khubalkar
- Teacher: Sunantha Krishnan
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- Teacher: Prasad Padalkar
- Teacher: Sunantha Krishnan
- Teacher: Prasad Padalkar