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Dec 12, 2024
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CSD 438 Big Data Application Development5 credits Students are introduced to techniques and tools used to manage, process, and interact with massive datasets. The course explores non-relational (NoSQL) data storage for big data applications. The course covers topics such as distributed data storage, MapReduce, key value stores, stream processing, data mining, and basic statistical techniques to perform data analytics.
Prerequisites: CSD 331 , CSD 425 , and admission to the BAS IT:CSD program
Course Outcomes Upon successful completion of this course students will be able to:
- Explain the fundamentals of big data and analytics
- Implement data pipelines to integrate data from a variety of sources
- Use publish-subscribe and message queue models to acquire data
- Run batch analytics using the MapReduce programming model
- Perform real-time analysis using Apache Spark and Storm
- Implement reporting APIs and dashboards
Program Outcomes This course teaches to the following program outcomes:
- demonstrate competency in software engineering, software testing principles, and quality assurance techniques
- implement program management concepts
- identify, evaluate, and apply efficient algorithms and technologies required for developing software system
- demonstrate ability to understand and integrate contributions to the architecture design of a large software system
- be prepared to obtain an entry-level position at a software development company
Total Hours: 60 Theory (Lecture) Hours: 40 Guided Practice (Lab or Clinical) Hours: 20
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