MATH 0216

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. 3 hrs lect./disc.
Natural Sciences
Requirements Fulfilled:
Equivalent Courses:
MATH 0118 *


Spring 2021

MATH0216A-S21 Lecture (Lyford)
MATH0216B-S21 Lecture (Karpman)

Fall 2020

MATH0216A-F20 Lecture (Lyford)
MATH0216B-F20 Lecture (Karpman)
MATH0216C-F20 Lecture (Lyford)
MATH0216Y-F20 Lab (Lyford)
MATH0216Z-F20 Lab (Lyford)

Spring 2020

MATH0216A-S20 Lecture (Malcolm-White)

Fall 2019

MATH0216A-F19 Lecture (Lyford)
MATH0216B-F19 Lecture (Lyford)

Spring 2019

MATH0216A-S19 Lecture (Lyford)
MATH0216B-S19 Lecture (Lyford)

Fall 2018

MATH0216A-F18 Lecture (Lyford)

Spring 2018

MATH0216A-S18 Lecture (Lyford)

Fall 2017

MATH0216A-F17 Lecture (Lyford)

Fall 2016

MATH0216A-F16 Lecture (Kim)

Spring 2016

MATH0216A-S16 Lecture (Kim)