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Course Descriptions

DATA 199 Topics in Data Science (1-4)

A semester-long study of topics in Data Science. Topics and emphases will vary according to the instructor. This course may be repeated for credit with different topics. See the New and Topics Courses page on the Registrar’s webpage for descriptions and applicability to majors/minors in other departments.

  • General Education Requirement Fulfillment: Topic dependent
  • Prerequisite: Topic dependent
  • Offering: Occasionally
  • Professor: Staff

DATA 299 Topics in Data Science (1-4)

A semester-long study of topics in Data Science. Topics and emphases will vary according to the instructor. This course may be repeated for credit with different topics. See the New and Topics Courses page on the Registrar’s webpage for descriptions and applicability to majors/minors in other departments.

  • General Education Requirement Fulfillment: Topic dependent
  • Prerequisite: Topic dependent
  • Offering: Occasionally
  • Professor: Staff

DATA 375 Problem-Solving with Data Analytics (4)

Students will work in teams to apply data analytics tools and skills toward the resolution of a question or problem. Depending on the instructor, this course might organize all projects around a common question, problem, or challenge, or it might allow teams to identify a theme of their own. Teams will work with the instructor to develop a problem-solving strategy that utilizes the data-analytics skills and methods acquired in prerequisite courses, to develop a project plan, and to carry out the project. In most instances, projects will yield a summary essay, research paper, or white paper.

  • General Education Requirement Fulfillment: Math Sciences
  • Prerequisite: CS 151, MATH 239, CS 370, and one elective from the Data Science minor applied data analysis or statistical and mathematical theory categories
  • Offering: Annually
  • Instructor: Strawn, Staff

DATA 399 Topics in Data Science (1-4)

A semester-long study of topics in Data Science. Topics and emphases will vary according to the instructor. This course may be repeated for credit with different topics. See the New and Topics Courses page on the Registrar’s webpage for descriptions and applicability to majors/minors in other departments..

  • General Education Requirement Fulfillment: Topic dependent
  • Prerequisite: Topic dependent
  • Offering: Occasionally
  • Professor: Staff

DATA 429 Topics in Data Science (1-4)

A semester-long study of topics in Data Science. Topics and emphases will vary according to the instructor. This course may be repeated for credit with different topics. See the New and Topics Courses page on the Registrar’s webpage for descriptions and applicability to majors/minors in other departments.

  • General Education Requirement Fulfillment: Topic dependent
  • Prerequisite: Topic dependent
  • Offering: Occasionally
  • Professor: Staff

DATA 499W Independent Internship or Thesis

Course in development.


DATA 501 Foundations of Data Science with R (4)

This foundational course offers a full-spectrum introduction to data science and data science workflows, emphasizing data as a source of value creation in the enterprise. The R programming environment serves as the implementation vehicle in support of essential data science activities – data exploration and visualization, data wrangling, predictive modeling, model deployment, and communication. The R programming environment, along with Python, is among the most important tools in the data scientist’s toolbox and this course will feature tools and a style of programming inspired by the popular tidyverse ecosystem – ggplot2 for data visualization, dplyr and tidyr for data wrangling. Students will master elements of the data science workflow through a series of short R programming exercises reinforced by a full-spectrum, integrative final project. Presentation skills are an ever-present theme as students are challenged, through every stage of analysis, to communicate managerial relevance and value to the enterprise.

  • Prerequisite: None
  • Offering: Fall
  • Professor: Staff

DATA 502 Data Visualization and Presentation (4)

It’s one thing to conduct an analysis, it’s another to convince someone to change their behavior based on this analysis. In this course, students will study theories of visualization, communication and presentation with the purpose of translating technical results into actionable insight. Using a mix of case studies and code, the course begins with an examination of how to ask good research questions. It then covers the psychology of communication and the construction of compelling visualizations. Finally, students are tasked with writing and presenting their work in a manner suited to a non-technical audience.

  • Prerequisite: None
  • Offering: Fall
  • Professor: Staff

DATA 503 Fundamentals of Data Engineering (4)

Data management is core to both applied computer science and data science. This includes storing, managing, and processing datasets of varying sizes and types. This course introduces students to the various ways in which data is stored and processed including relational databases, file-based databases, cloud-based storage and data streaming. A key component of the course is learning which architectures fit which types of data science problem (and the strengths and weaknesses of each). Students will learn to work with data that is both clean and structured, and dirty and unstructured.

  • Prerequisite: None
  • Offering: Spring
  • Professor: Staff

DATA 504 Data Ethics, Policy and Human Beings (4)

This course explores the legal, policy, and ethical implications of data. These types of issue arise at each stage of the data science workflow including data collection, storage, processing, analysis and use. Armed with legal and ethical guidelines, students are then confronted with topics including privacy, surveillance, security, classification, discrimination, decisional-autonomy, and duties to warn or act. Using case studies and a lecture-discussion format, the course will address real-world problems in areas like criminal justice, national security, health, marketing and politics.

  • Prerequisite: None
  • Offering: Spring Semester
  • Professor: Staff

DATA 505 Applied Machine Learning (4)

Machine learning is becoming a core component of many modern organizational processes. It is a growing field at the intersection of computer science and statistics focused on finding patterns in data. Prominent applications include personalized recommendations, image processing and speech recognition. This course will focus on the application of existing machine learning libraries to practical problems faced by organizations. Through lectures, cases and programming projects, students will learn how to use machine learning to solve real world problems, run evaluations and interpret their results.

  • Prerequisite: None
  • Offering: Spring
  • Professor: Staff

DATA 510 Capstone Project (4)

Over the course of the semester, students will propose, plan and execute an actual data science project. Run as an independent study during the student’s last term, the project provides an opportunity to integrate all of the core skills learned throughout the program, and to develop a portfolio piece that can help with students’ career aspirations. Projects must be consequential in nature—i.e., have a real (or potential) impact on some organization, or the world. Grades will be based on assessments by both the faculty advisor and those (potentially) impacted by the project’s results. Data sets must be selected by the student either from a public repository or from the company for which they work and approved by the course instructor within the first two weeks of the term.

  • Prerequisite: None
  • Offering: Summer
  • Professor: Staff

DATA 520 Marketing Analytics (4)

  • Offering: TBD
  • Professor: Staff

DATA 521 Time Series Modeling (4)

  • Offering: TBD
  • Professor: Staff

DATA 522 Python Programming (4)

  • Offering: TBD
  • Professor: Staff

Willamette University

3+1 BS/MS in Data Science

Address
900 State Street
Salem Oregon 97301 U.S.A.
Phone
503-370-6724