BIOSTAT625: Computing with Big Data
- Graduate level
- Fall term(s) for residential students;
- 3 credit hour(s) for residential students;
- Instructor(s): Jiang, Hui (Residential);
- Prerequisites: R module in BIOSTAT 607 or equivalent.
- Description: This course will cover techniques for computing with big data. The topics include programming, data processing, debugging, profiling and optimization, version control, software development, interfacing with databases, interfacing between programming languages, visualization, high performance and cloud computing. Hands-on experience will be emphasized in lectures, homework assignments and projects.
- Learning Objectives: (a) To master techniques for manipulating and processing big data by writing customized computer programs. (b) To understand the foundation for the computing aspects of data science. (c) To have a practical understanding of important computing issues for health big data analysis.
- Syllabus for BIOSTAT625
|Department||Program||Degree||Competency||Specific course(s) that allow assessment||BIOSTAT||Health Data Science||MS||Apply basic informatics and computational techniques in the analysis of big health data, and interpret results of statistical analysis||BIOSTAT625|