MATH0216A-S16
Introduction to Data Science
Introduction to Data Science
In this course students will gain exposure to the entire data science pipeline: forming a statistical question, collecting and cleaning data sets, performing exploratory data analyses, identifying appropriate statistical techniques, and communicating the results, all the while leaning heavily on open source computational tools, in particular the R statistical software language. We will focus on analyzing real, messy, and large data sets, requiring the use of advanced data manipulation/wrangling and data visualization packages. Students will be required to bring their own laptops as many lectures will involve in-class computational activities. (MATH 0116; or ECON 0210 or PSYC 0201 and experience with R) 3 hrs lect./disc.
In this course students will gain exposure to the entire data science pipeline: forming a statistical question, collecting and cleaning data sets, performing exploratory data analyses, identifying appropriate statistical techniques, and communicating the results, all the while leaning heavily on open source computational tools, in particular the R statistical software language. We will focus on analyzing real, messy, and large data sets, requiring the use of advanced data manipulation/wrangling and data visualization packages. Students will be required to bring their own laptops as many lectures will involve in-class computational activities. (MATH 0116; or ECON 0210 or PSYC 0201 and experience with R) 3 hrs lect./disc.
- Term:
- Spring 2016
- Location:
- Warner Hall 506(WNS 506)
- Schedule:
- 11:15am-12:05pm on Monday, Wednesday, Friday (Feb 15, 2016 to May 16, 2016)
- Type:
- Lecture
- Instructors:
- Albert Kim
- Subject:
- Mathematics
- Department:
- Mathematics
- Division:
- Natural Sciences
- Requirements Fulfilled:
- CW DED
- Levels:
- Undergraduate
- Availability:
- View availability, prerequisites, and other requirements.
- Course Reference Number (CRN):
- 22427
- Subject Code:
- MATH
- Course Number:
- 0216
- Section Identifier:
- A