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Big Data Organization and Management

General

Prefix

SE

Course Number

413

Course Level

Undergraduate

College/School

College of Science and Engineering

Description

Data analytics concepts and techniques. Big-data features and representations, data collection and sampling, predicative modeling, frequent patterns, social networks analysis, data benchmarking and privacy, data modeling and documentation.

Prerequisites

Credits

Min

3

Max

3

Repeatable

No

Goals and Diversity

MN Goal Course

No

Cultural Diversity

No

Learning Outcomes

Outcome

Identify the characteristics of big data.

Outcome

Apply concepts of data collection, sampling, and pre-processing techniques.

Outcome

Apply predictive analysis techniques.

Outcome

Use descriptive analysis techniques, including association rules, sequence rules, and segmentation.

Outcome

Apply analysis to social networks.

Outcome

Evaluate benchmarking, data quality, privacy, software and model design and documentation.

Course Outline

Course Outline

Big-data features. 10% Data collection and sampling. 10% Data pre-processing. 10% Predictive modeling and its algorithms. 15% Descriptive analysis techniques. 15% Analysis on social networks. 10% Benchmarking, data quality and data privacy. 15% Software design and documentation. 15%

Dependencies

Programs

SE413 is a completion requirement for: