The Data Science degree option is part of the Bachelor of Science in Human Centered Design & Engineering degree program.
Planned Retirement of the Data Science Option
The HCDE faculty have voted to suspend admission to the Data Science Option effective Winter 2024. HCDE undergraduates who are admitted after Autumn 2023 will not be eligible to declare the Data Science Option. HCDE undergraduates who were admitted Autumn 2023 or earlier who wish to declare the Data Science Option must schedule an appointment with HCDE BS Advising no later than Dec. 8, 2023 (and no later than the 3rd Friday of the quarter in which they wish to graduate, if they will graduate before this date). The HCDE Department will not approve late degree option changes that would extend a student’s graduation beyond what is permitted by UW’s Satisfactory Progress Policy and the HCDE Continuation Policy.
Questions regarding the upcoming retirement of the Data Science Option can be directed to HCDE BS Advising.
What is Data Science?
The emerging field of Data Science encompasses a broad set of interdisciplinary skills including data management, programming, statistics, machine learning, visualization, and human-centered design. In today's workforce there is increasing demand for a new class of data scientists with expertise in managing, modeling, and visualizing the massive, noisy, and heterogeneous datasets that arise across many areas of science and industry.
The University of Washington has become a leader in the inclusion of human-centered skills in Data Science curriculum. The Data Science degree option in the Department of Human Centered Design & Engineering will educate undergraduate students in all aspects of the field of Data Science, increase their marketability in the workplace, and enable them to contribute to solutions to the many critical data-intensive problems in the world today.
Requirements for the Data Science Degree Option
To meet the requirements for the Data Science option, students must take a minimum of 25 credits from the approved list of courses:
- HCDE 411 Information Visualization (5)
- SOC 225 Data and Society (3/5)
- One course from CSE 123 Introduction to Computer Programming III or CSE 143 Computer Programming II (Note: This course satisfies the Engineering Fundamentals requirement and is not included in the overall credit requirement)
- One course from each of the following Data Science course areas, listed below.
Students take additional approved HCDE elective courses to reach 25 credits minimum for the degree option.
Data Science Course Areas
- CSE 416/STAT 416 Introduction to Machine Learning (4)
- INFO 371 Advanced Methods in Data Science (5)
- STAT 435 Introduction to Statistical Machine Learning (4)
- STAT 390 Statistical Methods in Engineering and Science (4)
- STAT 403/Q SCI 403 Introduction to Resampling Inference (4)
- STAT 425/BIOST 425 Introduction to Nonparametric Statistics (3)
Degree Planning for the Data Science Option
While the courses listed above are approved to count towards the HCDE Data Science Option course areas, some of these courses have prerequisites that most HCDE students have not taken or are frequently restricted to students in their own majors. Because of this, the overwhelming majority of students who graduate with the HCDE Data Science Option complete the Option course areas by taking CSE 416, CSE 414, and STAT 390.
The HCDE Department does not control the scheduling for non-HCDE courses and cannot guarantee that they will not conflict in timing with HCDE courses. Students who encounter scheduling challenges when planning their option coursework can meet with HCDE Advising for assistance with their degree plans, but are encouraged to consider instead pursuing our more flexible Standard Option. Students pursuing the Standard Option with an interest in data science may wish to consider the Data Science minor, which offers more flexible course options and a wider variety of topics to choose from. Students interested in the minor should meet with HCDE Advising to review your plan to determine whether you have space to fit in the minor within UW's Satisfactory Progress guidelines.