SE513 - Big Data Organization and Management
General
- Prefix
- SE
- Course Number
- 513
- Course ID
- 00184719
- Course Level
- Graduate
- Instruction Mode
- Lecture
- Department(s)
- Computer Science/Information Technology
- 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. Prereq.: SE 512.
- Cross Listed Courses
Prerequisites
No Requisites
Credits
- Min
- 3
- Max
- 3
- Repeatable
- No
Goals and Diversity
- MN Goal Course
- No
- MN Goal Designation(s)
- -
- 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.
Dependencies
No dependencies