Data Science Certificate

The Data Science certificate provides foundational data analysis and programming skills for high-end users of data science tools. It does not require any calculus, only fulfillment of Quantitative Reasoning A. Having some math or algebra background is helpful. It is a great fit if you want to apply your Data Science skills to specific areas such as your major or a career field you are interested in pursuing post-graduation.

The Data Science major combines advanced math and programming skills to solve data rich problems, develop data science tools and produce meaningful insights from data. It requires Calculus 1, Calculus 2, and a linear algebra course. It is a great fit if you are interested in analyzing data on all scales such as building algorithms, math underpinnings, and video programming.

In summary, the certificate is a good fit if you will be a high-end user of data tools and the major is a good fit if you want to be a developer of data tools.

If you want to learn data analysis, you can do that with learning R and Python with the Data Science certificate. If you want to develop more computer science skills like computer engineering, software design, etc. then it would make sense to do the Computer Science certificate to learn Java.

In summary, DS works more in analytics and using data to answer questions whereas CS is more technical application and web development in creating computing tools. It really depends on what skill set you hope to develop.

Statistics provides a mathematical approach to answering data questions at all scales. The Statistics certificate is a good fit for students who want to develop knowledge in statistical skills and analysis to apply it to their major or field (e.g. conducting field trials). Students are required to be proficient in math and statistics.

Data Science provides a computational approach to answering large data questions. The Data Science certificate provides foundational data analysis and programming skills for high-end users of data science tools (e.g. doing large scale genomic analysis). It does not require any calculus, only fulfillment of Quantitative Reasoning A but having some math or algebra background is helpful.

Both certificates provide skills in extracting and analyzing data. It really depends on if you want to develop statistical analysis skills with a foundational background in math or data analysis skills with a foundation in computer programming.

There are no repercussions for cancelling the Data Science certificate. Majors and certificates only appear on your transcript for the academic terms for which you are declared in (there is no DR notation like a dropped course). Students are encouraged to submit the cancellation form if they no longer wish to continue the certificate.

Completion of math or statistics is not a requirement to declare the certificate. However, having completion of calculus 1 or introductory statistics can provide more elective options so that you are able to complete the certificate. If math or statistics is a concern, please schedule a Starfish appointment with the certificate advisor to discuss your course options.

Math: We do not require any level of math, only fulfillment of Quantitative Reasoning A (QR-A). If you plan to enroll in STAT 340 Data Science Modeling II to fulfill an elective requirement, you must have MATH 211, 217, 221, or 275 completed.

Statistics: The only introductory statistics course that counts for the certificate is STAT 240. If you have taken STAT 301 or 371, they meet requisites for some of our domain electives. Click here to view the differences between our introductory statistics courses.

Completion of a programming course is not a requirement to declare the certificate.

All three of our introductory programming courses (COMP SCI 220, STAT 240, and E C E 204) presume no previous programming or coding background. COMP SCI 220 and E C E 204 are Python programming courses and STAT 240 is R programming.

Students who have COMP SCI 300 completed, should take COMP SCI 320 as their foundation course.

Students are required to take two electives that add up to at least six credits. There are two options for completing certificate electives:

• Option 1: Take one fundamental elective and one domain elective
• Option 2: Take two fundamental electives

Fundamental electives build more directly on existing skills of foundation courses whereas Domain electives where you use your DS skills to apply it to a specific area or field.

Yes, you are welcome to take courses that count for both your major and the Data Science certificate.

Please send a syllabi and your rationale for counting it as an elective to the dscert@stat.wisc.edu email. Your request will then be forwarded to the Data Science Programs Committee (DSPC) for review. The decision process will take 2-3 months approximately.

We do not allow any substitutions for STAT 240. Click here to view the differences between our introductory statistics courses.

Though STAT 301, 324, and 371 teaches introductory statistics, STAT 240 different because it is a 4 credit course focusing in depth on the R programming language, data management, analysis, and modeling. Students who have taken STAT 324 previously will be well prepared for STAT 240 and will learn additional concepts that will prepare them for future courses such as STAT 340.

If your major requires a Statistics course and you are interested in the Data Science certificate, please check with your major advisor if STAT 240 can fulfill your major’s statistics requirement.

Please note that STAT 240 is not a required course for the certificate. If you wish to not take STAT 240, you can opt to take E C E 204 and COMP SCI 220 to fulfill the two courses needed for the foundation programming requirement.

COMP SCI 220 is first semester Python where you will learn the Python program and data management. COMP SCI 300 is Java II where you will learn the Java program and build basic computer science skills to prepare you for future CS courses. COMP SCI 320 is second semester Python which requires completion or COMP SCI 300 or COMP SCI 220.

We do not recommend taking COMP SCI 220 and 300 in the same semester since they are really intensive coding classes and has similar content. Students who love coding are welcome to take the Python sequence of COMP SCI 220 and 320. By taking this route, COMP SCI 220 will fulfill a foundation programming requirement and COMP SCI 320 will fulfill an elective for the Data Science certificate.

Students who have taken COMP SCI 300 before or in the Computer Sciences major, can continue on to COMP SCI 320. By taking only COMP SCI 320 (and not 220), then COMP SCI 320 will fulfill a foundation programming requirement. You will then need to identify two elective courses, one programming course, and L I S 461 to finish the rest of the Data Science certificate requirements. A reminder that COMP SCI 320 can only count for either foundation programming or elective, not both.

L I S 461 can be taken for 3 or 4 credits depending on what requirements you want it to count for (Communication B and/or Humanities). Please pay careful attention when enrolling, students cannot switch sections if they enroll in the incorrect section.

Taking it for 3 credits (also known as the non-ComB section) will count as Humanities with one lecture section and no discussion section. This is best for students who (1) have completed ComB, (2) in the School of Business since they will take GEN BUS 360 to fulfill ComB, or (3) in the College of Engineering since they will take INTEREGR 397 to fulfill ComB

Taking it for 4 credits (also known as the ComB section) will count as Humanities and Communication B with one lecture and discussion section. Best for students who (1) still need to complete ComB or (2) still need at least 4 credits of Humanities to meet their B.A./B.S. degree requirements.

Priority to enroll in this course is reserved for students declared in Information Science Major, Data Science Major, or Data Science Certificate. Please plan ahead and complete the Data Science certificate declaration process before trying to enroll in the course.

Due to course and instructor capacity, students are advised to take this course in their late junior year or senior year. L I S 461 is also currently the ONLY data ethics course that is required for the Data Science major and certificate.

First think about what field or domain area you wish to learn more about or apply your foundational DS skills to. View all of our elective course options on the Guide here and note any course titles or course descriptions that speak to your interests. It is also important to view if you meet the prerequisites to enroll in those elective courses so that you can plan ahead if you are missing a prerequisite.

If you have questions or concerns about meeting prerequisites for elective courses, schedule a Starfish appointment with the certificate advisor to discuss your options. Always consult the semesterly enrollment newsletter (see planning your data science certificate section above) in case there are newly approved elective courses that might better fit your interests or graduation timeline.

Please see the Department of Statistics page on undergraduate research for more information about how to find research opportunities as an undergraduate at UW-Madison. Students can also explore the following research resources too.

• Discovery Portal http://discoveryportal.org/default.aspx
• UW Experts Guide http://experts.news.wisc.edu/
• UW Departments http://www.wisc.edu/academics/
• UW Research Centers https://research.wisc.edu/centers-cores/more-uw-research-centers-and-programs/
• Student Job Center https://jobcenter.wisc.edu/

Student organizations are a great way for Data Science students to get involved on campus. Find a list of current student organizations on the Wisconsin Involvement Network (WIN) website.  Use keywords that interest you when searching for organizations like “data,” “statistics,” “computer science,” “coding,” etc. Several student orgs that DS students may take an interest in are:

• dotData (Data Science Club)
• Undergraduate Statistics Club of UW-Madison
• Economics Student Association
• Girls Who Code

You may also check out the CDIS student organizations page here.

A great place to start is exploring the Major and Certificate Advising Page for Data Science. At the bottom of that page, there is a list of study abroad programs that students have been able to earn credits for the Data Science certificate. Typical courses that Data Science students take abroad are breadth courses, language courses, and data science elective courses including upper level Computer Sciences, Mathematics, or Statistics courses. We also recommend consulting with Study Abroad advisors for assistance with identifying and applying to programs that may have relevant Data Science courses.

SuccessWorks is the career services unit for L&S students and a fantastic partner and resource for career and internship assistance. Data Science is part of the Technology, Data & Analytics Career Community.

We have a Career Pathways canvas course for students interested in graduate school and career exploration in Data Science.

We strongly recommend checking out our Student Career Resources page for great resources and reading the weekly newsletter (once you are declared) for upcoming events.