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Declaring the Minor in Data Science

Process for Declaring the Minor

The assignment of students to a Data Science Minor Cohort and declaration of the minor happens annually in spring quarter.

Students who declare are assigned to a Data Science Minor Cohort that reflects the academic year the students in the cohort are assigned to take their 4 core Data Science courses and the track, R or Python, that they will take the courses in.

Assignment to a cohort is based on availability, track preference, and other factors. Students are only guaranteed seats in the 4 core data science courses in their assigned Cohort year.

For students who are trying to decide if they will pursue the Major in Data Science or the Minor in Data Science, we recommend adding yourself to The Data Science Interest List as early as possible so you will be prepared for the spring declaration period for the minor while simultaneously taking the 3 foundational courses for the major, preferably in the Fall and Winter quarters.

Students who wish to declare the Minor in Data Science will follow these steps

Step 1: Review the Requirements

Review the course requirements for the Minor in Data Science

Step 2: Add yourself to The Data Science Interest List as early in the academic year as possible.

All students are encouraged to join the list as early as possible as the date a student signs up is taken into consideration when making assignments to cohorts and track. Incoming first year students interested in the minor should join the Data Science Interest List in Fall quarter of their first year.

The 2023 Data Science Interest List opens on September 1, 2022, with Minor in Data Science Information Sessions held in early April 2023.

2023 Data Science Interest List

The 2023 Data Science Interest List will close on March 31, 2023, and Minor in Data Science Information Sessions will be held the week of April 3.

The Data Science Interest List is for students interested in declaring the Minor in Data Science in Spring, students who are interested in the Major in Data Science but have not yet completed the 3 required foundational courses, and students who are trying to decide between the major and the minor.

Students on the Data Science Interest List will receive periodic emails from the department throughout fall and winter quarter with information related to what they have indicated interest in.

Step 3: Talk with your Academic Advisor

This step is optional but highly recommended.

Meet with your Academic Advisor prior to spring quarter to discuss your academic plan and decide which cohort year or years for the minor you have available in your schedule. Remember you will be doing all 4 core STAT data science minor courses in the same academic year, which requires you to be able to take courses in Fall, Winter, and Spring of that academic year.

If you are considering doing off campus study, please take that into consideration when selecting possible cohort years.

Additionally, you may wish to seek advice from your major/minor/certificate advisors on cohort availability or R/Python track selection as it relates to your future goals.

Please keep in mind that your Advisors can only tell you whether taking the required courses for the minor is viable in a given academic year, they do not assign you to a cohort. Your cohort and track will be assigned to you by the Department of Statistics and Data Science after you attend the required information session and complete the necessary form where you will indicate which cohorts you are available for and what track you wish to take the sequence courses in (see step 5).

Step 4: Prepare for taking the Data Science sequence courses

Students should have their introductory statistics course completed prior to spring quarter if they are hoping to take the Data Science sequence in the following academic year. We highly recommend taking the introductory statistics course in either Fall or Winter quarter to ensure completion of the requirement in time.

Students are also encouraged to determine which track, R or Python, they would like to take the Data Science sequence in as early as possible since having some knowledge of the programming language prior to starting the Data Science courses is strongly encouraged, especially for students interested in the Python track. See the R & Python Learning Resources page for more information on the differences between R and Python and learning opportunities.

Step 5: Attend a Required Minor in Data Science Information Session in Spring Quarter and complete the declaration process.

Held in spring quarter, typically in April, these sessions prepare students for all the aspects of declaring the minor and attending one is a required step in declaring the minor. Students must add themselves to the Data Science Interest List to receive information about registering for a Minor in Data Science Information Session. Again, we encourage students to add themselves to the Data Science Minor Interest List as early as possible.

At the end of the information session, students who want to declare the minor will submit their cohort year availability and track preference via the provided link. Students must complete this form to be assigned to a cohort and track. If you are interested in declaring the minor do not exit the session without completing the provided form.

After all the information sessions in spring quarter have concluded, students will be assigned to cohorts and tracks and emailed information on how to set up their individual advising session to finish their declaration of the minor.

Reminder: students are only guaranteed seats in the 4 core data science courses (the Data Science Sequence and STAT 302) in their assigned Cohort year and in their assigned track. Declared students may petition to change their Cohort year, track, sequence class section, or 302 quarter after assignment, but changes are subject to seat availability. Note, students may only petition to change tracks prior to starting the sequence courses. Once they have started the sequence, they are no longer permitted to change tracks.

 

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