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Big Data: Tools and Techniques (ISSS612)

Course description

This course is designed to prepare students to work on novel business or technical problems relating to extremely large or extremely high-frequency data. Common examples are recommendation systems in e-commerce, fraud detection systems in Finance, or large-scale stream analytics for Internet of Things and distributed sensor data. There will be a variety of techniques presented, and students will develop functional prototypes to solve real-world problems.


Seminar Required

Graded, 1.0 Credit Units

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