Data Science Options

The Data Science options provide students an introduction to the world of data science, giving them the skills to understand a variety of techniques and tools. The goal of this option is to educate all students in the foundations of data science, so they may apply those methods and techniques in current research. There are two options, the Data Science Option (DSO) and the Advanced Data Science Option (ADSO). If you have questions about the DSO/ADSO or getting into classes, please speak with Ariel Rokem (arokem@uw.edu).

Students

Eligible students for the DSO and ADSO include all full time Ph.D. students in the Psychology program in good standing who have completed the first year statistics requirements and who have permission of their advisors. Please complete the DSO/ADSO form, have your advisor and co-advisor sign it, and return it to the Grad Program Advisor by the time you complete your first DSO/ADSO course. If your advisor will not approve your request to do the DSO/ADSO, a student can write a letter of appeal to the GTC.

In cases where a graduate student does not graduate but instead leaves only after completing the master’s part of the graduate program, the student will retain the “Data Science option” or “Advanced Data Science option” recognition on their transcript if the student finishes all the requirements of the option before leaving the graduate program.

The Data Science Option (DSO)

The Psych DSO is designed for students with little or no background in data science, computer science or coding. The total credit requirement is 6-8 credits in courses (2 courses @ 3-4 credits each) and 2 seminar credits (plus the usual Psych 522-525 sequence). Note that one of the data science courses may count as your third required quantitative course for the Psychology PhD if approved by the Psychology quant area, resulting in only one “extra” course (and 2 quarters of seminar) beyond the usual Psychology quantitative requirements.

The “third” course can also count toward a Quant minor but all other classes must be unique if a student opts for the DSO and Quant minor.

The requirements for the Psych DSO are as follows:

  1. Courses from two out of three of the following areas:
    1. Software development for data science
      • HIGHLY RECOMMENDED:
        • Software Development for Data Scientists (CSE 583)
        • Software Engineering for Molecular Data Scientists (ChemE 546)
        • Informatics in Psychology (PSYCH 532)
    2. Statistics and machine learning
      • HIGHLY RECOMMENDED:
        • Introduction to Machine Learning (CSE 416/STAT416)
      • ALTERNATIVE:
        • Nonparametric regression and classification (STAT 527)
      • ADVANCED OPTION:
        • Machine Learning: (CSE 546 or STAT 535) also serves for the “Advanced Data Science Option”
        • Introduction to Mathematical Statistics (STAT 509) and Statistical Inference (STAT 512-513) also serves for the “Advanced Data Science Option”
    3. Data management and data visualization
      • HIGHLY RECOMMENDED:
        • Introduction to Database Systems (CSE 414)
        • Information for Visualization (HCDE 411/511)
      • ADVANCED OPTION:
        • Principles of DBMS (CSE 544) also serves for the “Advanced Data Science Option”
        • Data Visualization (CSE 512) also serves for the “Advanced Data Science Option”
  2. 2 quarters of the eScience Community Seminar (https://escience.washington.edu/connect/events/uwdss/)
  3. Fulfillment of the Psychology Department Statistics and General Methodology requirements. These are currently the following (students must achieve a 2.7 or above on each). Psych 522, Psych 523, Psych 524, Psych 525 (If a student places out of one or more of these, they must take a higher-level course in its place and it cannot count as another of the DSO courses). Note that one of the data science courses may count as your third required quantitative course for the Psychology PhD if approved by the Psychology quant area, resulting in only one “extra” course (and 2 quarters of seminar) beyond the usual Psychology quantitative requirements.

Advanced Data Science Option (ADSO)

The “Advanced Data Science” option aims to educate the next generation of thought leaders who will both build and apply new methods for data science. This option will help to educate and recognize PhD students whose thesis work focuses specifically on building and using advanced data science tools. The goal of this option is to provide advanced education to the students who will push the state-of-the-art in data science methods in the domain of Psychology.

The ADSO is designed for students with a significant CS background. It is strongly recommended that you look carefully at class syllabi before requesting the ASDO option.

The total credit requirement is 10-12 credits in courses (3 courses @ 3-4 credits each) and 4 seminar credits (plus the usual Psych 522-525 sequence). Note that one of the data science courses may count as your third required quantitative course for the Psychology PhD if approved by the Psychology quant area, resulting in only two “extra” courses (and 4 quarters of seminar) beyond the usual Psychology quantitative requirements. The course that counts as the third quant course for the Psych PhD can also count toward a Quant minor however all other courses need to be unique for the ADSO and Quant Minor.

The requirements for the Psych ADSO are as follows:

  1. Three out of the following four courses:
    • Principles of DBMS: CSE 544.
    • Machine Learning or Statistical Learning, CSE 546 or STAT 535.
    • Data Visualization: CSE 512.
    • Introduction to Mathematical Statistics or Statistical Inference: STAT 509 or STAT 512-513.
  2. 4 quarters of the eScience Community Seminar (https://escience.washington.edu/connect/events/uwdss/)
  3. Fulfillment of the Psychology Department Statistics and General Methodology requirements. These are currently the following (students must achieve a 2.7 or above on each). Psych 522, Psych 523, Psych 524, Psych 525 (If a student places out of one or more of these, they must take a higher level course in its place and it cannot count as another of the DSO courses). Note that one of the data science courses may count as your third required quantitative course for the Psychology PhD if approved by the Psychology quant area, resulting in only two “extra” courses (and 4 quarters of seminar) beyond the usual Psychology quantitative requirements.

FAQ

What’s an option? Is it real?

The option is ‘accredited’ by the graduate school and goes on your official graduate transcript.

What’s the relationship between the DSO and the quant minor?

The quant minor is a psychology department offering focused on the kinds of statistics utilized within psychology and related fields, whereas the data science option is focused on statistical learning from a machine learning perspective which includes topics like database management and software development.

Most of the 500 level classes in the statistics and machine learning domain of the DSO will ALSO count for credit for the quant minor. Most of the classes in the topics of software development, data management or data visualization will not count towards the quant minor. If you have questions about whether a class will count towards your quant minor please email Brian Flaherty (bxf4@u.washington.edu)

All the classes I want to take are full!

Expect classes to be heavily subscribed. Register early. If you are really running into difficulties, then email Ariel Rokem (arokem@uw.edu) explaining which class you need to take.

A lot of these classes have pre-requisites

Many classes have pre-requisites. You will need to contact the instructor to ask if you can get those waived or you will need to take the pre-requisites.

Where is the declaration form?

You can download it here. Remember, this form is for you to declare the option with your existing program of study and that you have approval from your advisors (and Ariel Rokem, arokem@uw.edu, for the advanced option). There are additional requirements to actually complete the option and have it appear on your transcript. Return the completed form to the Grad Program Advisor.

Data science oriented fellowships:

Note that many of these fellowships require a nomination from the department, so you should assume that the application process begins at least 3  months before the sponsor deadline.

APPLE SCHOLARS IN AI/ML (Sponsor deadline likely to be announced in early August)

Created to celebrate the contributions of students pursuing cutting-edge fundamental and applied machine learning research worldwide.

https://machinelearning.apple.com/work-with-us#scholars 

GOOGLE PHD FELLOWSHIP (Sponsor deadline around early May)

Created to recognize outstanding graduate students doing exceptional and innovative research in areas relevant to computer science and related fields.

https://ai.google/research/outreach/phd-fellowship/ 

IBM PHD FELLOWSHIP (Sponsor deadline around November)

Recognizing and supporting exceptional PhD students that address focused areas of interest in technology.

https://www.ibm.com/developerworks/university/phdfellowship/

JP MORGAN AI RESEARCH PHD FELLOWSHIP (Announced around March)

https://www.jpmorgan.com/global/technology/ai/awards

TWO SIGMA PHD FELLOWSHIPS (Announced around Sept)

Supporting promising students who are engaged in innovative research in STEM fields.

https://www.twosigma.com/community/academic-partnerships/graduate-students/phd-fellowships/#:~:text=The%20faculty%20nomination%20process%20and,be%20decided%20by%20March%202024