EMSE 6574, SEction 11: Programming for Analytics
Course Information:
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Level:
Semester: Meeting Time: Meeting Place: Course page: |
Description:
This course provides a foundation in programming using the R programming language. Emphasis will be on producing clear, robust, and reasonably efficient code using top-down design, informal analysis, and effective testing and debugging. Throughout the course, students will primarily work on individual programming assignments to help practice problem solving skills, coding skills, and data science skills. Students will be assessed through quizzes, homework assignments, and exams. Teaching will involve interactive lectures with plenty of time spent live coding. This course assumes no prior programming experience and is an ideal preparation for higher level courses in data analytics.
Prerequisites:
None.
Learning Outcomes:Having successfully completed this course, students will be able to:
This course provides a foundation in programming using the R programming language. Emphasis will be on producing clear, robust, and reasonably efficient code using top-down design, informal analysis, and effective testing and debugging. Throughout the course, students will primarily work on individual programming assignments to help practice problem solving skills, coding skills, and data science skills. Students will be assessed through quizzes, homework assignments, and exams. Teaching will involve interactive lectures with plenty of time spent live coding. This course assumes no prior programming experience and is an ideal preparation for higher level courses in data analytics.
Prerequisites:
None.
Learning Outcomes:Having successfully completed this course, students will be able to:
- Write clear, robust, and reasonably efficient code in R using:
- Sequential, conditional, and loop statements.
- Multiple data types, including numeric, string, and logical data.
- Data structures, including vectors and data frames.
- Visualizations of data.
- Develop simple programs to effectively solve medium-sized tasks by:
- Employing modular, top-down design in program construction.
- Demonstrating an effective programming style based on established standards, practices, and guidelines.
- Proactively creating and writing test cases to test and debug code.
- Applying computational problem-solving skills to new problems.
- Import, manipulate, visualize, and export data in R.
