Welcome to Stats 295 - Scientific Computing with R
The course will introduce writing reproducible reports using R Markdown and version control. Students will write code to work with data that have different structures, format, and size and will learn practices to optimize code for efficiency. Students will develop data applications using Shiny and personal websites where they maintain their data science portfolio.
The course will introduce writing reproducible reports using R Markdown and version control. Students will write code to work with data that have different structures, format, and size and will learn practices to optimize code for efficiency. Students will develop data applications using Shiny and personal websites where they maintain their data science portfolio.
Course Goals
By the end of this course you will be able to:
By the end of this course you will be able to:
- write human- and machine-readable code using R.
- adopt reproducible workflow practices.
- develop and maintain R packages, Shiny apps, and websites;
Typical Week Workflow
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Monday 10:00 - 11:00 am
Dr. Dogucu holds office hours
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Monday 11 am
Weekly homework due
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Monday 11:00 am - 12:20 pm
Lecture
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Wednesday 11:00 am - 12:20 pm
Lecture
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Friday 3:00 - 4:00 pm
Dr. Dogucu holds office hours
Important Dates
Final project due December 10th at 10:00 am
R package due November 29th at 09:00 am
Final project proposal due Nov 8th at 09:00 am