BIG DATA ANALYTICS (4 Credits)

Learning Outcomes:

On successful completion of this course, students will be able to: Understand market and business drivers for big data, big data landscape, characteristics, and how it will impact to business; Identify big data issue to analyze, explain how to collect, store, and organize data using big data solution and recognize different data elements in everyday life problems also select the right data model and operation to suit data characteristics; Design, develop, and evaluate an end-to-end analytics solution combining large-scale data storage and processing frameworks; Design an approach to leverage data using the steps in the machine learning process and analyze big data problem using scalable machine learning algorithm; Design model for a problem into graph database and perform analytical over the graph in scalable manner; Build effective visual representation to provide better insight from big data

Topics:

1. Introduction to Big Data
2. Data Science: Getting Value out of Big Data
3. Big Data Foundation
4. Big Data Modeling
5. Big Data Management Systems
6. Big Data Integration
7. Big Data Processing
8. Spark Machine Learning Library
9. Introduction to Graphs
10. Graph Analytics for Big Data
11. Hadoop cluster & HDFS
12. Thesis supervision; Introduction to Big Data Integration (Guest Lecture)
13. Map reduce and Spark on YARN
14. Thesis supervision; Introduction to Visualization (Guest Lecture)