DATA 146: Introduction to Data Science

Course ID: DATA 146
Course Attribute: GE1
Title: Introduction to Data Science
Credit Hours: 3
Meeting Times: 11:00 to 11:50 MWF
Location: Remote Synchronous Off-Campus
Date Range: Spring Semester 2021

Course Description

This course will focus research design in the context of data, providing an overview of different modeling approaches, their differences, and the context(s) in which each might be most appropriate to apply. Special attention will be given to cases in which complete information is not available. Each modeling framework's disciplinary history will be considered, and the overlaps and distinctions between them discussed. Students will be expected to acquire a strong capability to identify the most appropriate modeling strategies given a problem and problem context, as well as learn the limitations or advantages of a given approach.

Courses Objectives (Overview)

In this course students will learn the fundamentals of data processing and modeling in the context of Data Science. Emphasis will be placed on careful planning and deliberate decision making when working with data and building models. Programming will be done in the Python language and we will be making extensive use of the scikit-learn collection. After learning about the basics of having a good Data Pipeline, students will be introduced to a variety of supervised and unsupervised machine-learning techniques including various methods for regression, classification, and clustering. By the end of the course, students are not expected to be an expert on any particular technique, but should exhibit a solid high-level understanding of the goals of each method, be able to determine when a particular type of model is more or less suitable to a real-world problem and, most importantly, demonstrate a keen attention to detail when working with data. Throughout the course, there will be a very strong emphasis placed on understanding why we are doing what we are doing.

Honor Code

Among our most significant traditions is the student-administered honor system. The Honor Code is an enduring tradition with a documented history that originates as far back as 1736. The essence of our honor system is individual responsibility. Today, students, such as yourself, administer the Honor pledge to each incoming student while also serving to educate faculty and administration on the relevance of the Code and its application to students’ lives.

The Pledge

“As a member of the William and Mary community, I pledge on my honor not to lie, cheat, or steal, either in my academic or personal life. I understand that such acts violate the Honor Code and undermine the community of trust, of which we are all stewards.”

Accessibility, Attendance & Universal Learning

William & Mary accommodates students with disabilities in accordance with federal laws and university policy. Any student who feels s/he may need accommodation based on the impact of a learning, psychiatric, physical, or chronic health diagnosis should contact Student Accessibility Services staff at 757-221-2509 or at sas@wm.edu to determine if accommodations are warranted and to obtain an official letter of accommodation. For more information, please see www.wm.edu/sas.

I am committed to the principle of universal learning. This means that our classroom, our virtual spaces, our practices, and our interactions be as inclusive as possible. Mutual respect, civility, and the ability to listen and observe others carefully are crucial to universal learning. Active, thoughtful, and respectful participation in all aspects of the course will make our time together as productive and engaging as possible.

Grade Categories

note .9 = .9 with bar notation

Grading Opportunities