Senior Capstone

The Capstone program represents the pinnacle of the undergraduate computer science, data science, and software development curriculums.  It is an intense two-semester sequence in which students embark either on their own research culminating with a Bachelor’s Thesis, or form project teams culminating in delivering a significant software Capstone Project.

Bachelor's Thesis

In CS 4940 – Undergraduate Research and CS 4970 – Bachelor’s Thesis, a student conducts research under the supervision of a faculty member and ultimately produces a publication quality description of the work. Both courses require permission of the thesis mentor to register. For more information, interested students can self-enroll in the Canvas course for Undergraduate Research and Thesis.

*Honors research thesis students must enroll in CS4999 (not CS4970) in their second semester of research work. For more information, self-enroll in the Canvas course linked above or contact the Honors Faculty Advisor: Professor Tom Henderson (tch@cs.utah.edu).

Capstone Project

During the Senior Capstone Project, small teams of students develop significant software systems using sound, disciplined software engineering practices on a project idea that they create.

CS 4000 – This class is the first semester in the sequence. Seniors will work on team formation, project identification, project planning (including UI design, software architecture, testing methods, scheduling, etc.), and work on the prototype. This course will provide teams with time and guidance to effectively plan their projects, as well as emphasizing the written and oral communications necessary to succeed in industry.

CS 4500. – Projects formed in CS 4000 must be completed during this semester. Students should have four or less CS electives/required courses left when signing up for this course and should be graduating at the end of the semester.

*Within the Capstone Project option, there are Clinical Capstone projects, sponsored by local industry, that will recruit students to work on a company specific project. View the CLINICAL CAPSTONE page for more details.

** Honors Capstone Project Thesis – An Honors student may do a capstone project, but must also write a separate project thesis which describes some aspect of the capstone project. The Honors Thesis Approval form must be submitted during the CS4000 semester, and the student must enroll in CS4998 while enrolled in CS4500.


Clinical Capstone Project

Overview of the Kahlert School of Computing Clinical Capstone Project

The Clinical Capstone Program matches a team of motivated senior undergraduate computer science students with an industry sponsored project, defined and funded by an industry sponsor.

The team of students completes the final two semesters of their degrees working toward realizing the sponsor’s idea.  Each team is advised by a School faculty member and works ~10 hours a week defining, researching, analyzing, and then producing a solution to meet the project’s objectives.

Thank You To Our Recent Sponsors

Ideal Clinical Capstone Project

The best projects have strong design elements that can help the students follow a rigorous process starting with creation of specifications, followed by creative concept generation and analysis, and culminating with a tested working prototype. Please propose your best idea, and we will work together to scope it correctly.


Timing

The two-semester Clinical Capstone Program is offered in two sequences:

  • Fall and Spring semesters (August start)
  • Spring and Fall semesters (January start)

At the end of each project, the teams participate in a Demo Day event, showcasing their work to faculty and industry judges, as well as fellow students.

Companies are encouraged to submit project proposals by August 1 for a Fall semester start, and December 1 for a Spring semester start. *We will meet with potential sponsors at any time, and sometimes late projects can be accepted.


How It Works

Faculty Advisor: Each team will have a faculty advisor guide them through the process with the industry sponsor.

Student Teams: Teams generally consist of 4 students.

Industry Sponsor Advisor: A representative from the industry sponsor is expected to serve as an advisor or co-advisor to help make sure the team stays on track to meet the project objectives. The industry sponsor advisor will typically spend an hour or less per week with the team – often meeting via web conference. At a minimum, a liaison from the company should meet periodically with the student team to provide feedback.

Design Reviews: Several design reviews occur during the two-semester project. The reviews provide critical feedback to the teams on all aspects of the project. Both the industry sponsor advisor and faculty advisor assist the team in understanding technical issues. Industry sponsors are encouraged to participate in the design reviews.

Presentations: Students showcase their work during several presentation opportunities throughout the year, and finally during a tradeshow-like format on Demo Day. They are also required to turn in a final report. Typically, they provide the sponsor with a working prototype and a documentation package (i.e. code, use instructions, etc.).


Important Dates

Step 1: Industry sponsor discusses project idea with clinical capstone faculty lead (by mid-July.)

Step 2: Industry sponsor submits project proposal (Early August)

Step 3: Project approved (by Aug. 15.)

Step 4: Contract signed and payment is processed (by Aug. 31.)

Step 5: Faculty advisor and student team is assigned (by Sept. 1.)

Step 6: Team works on project design, tests, and prototypes (throughout academic year.)

Step 7: Project completed, presented at Demo Day, and turned over to industry sponsor (at end of academic year.)


Project Deliverables

The project deliverables of a Clinical Capstone Project include a working prototype of the project and its code. Deliverables may be tailored in accordance with industry sponsor requirements.

Why Sponsor a Clinical Capstone Project?

Sponsoring a project allows you to contribute to educating the next generation of computer scientists by offering them a real-world industry experience.


What Should Sponsors Expect?

  • Get to know and evaluate students with specific interest in your company and industry.
  • Gain brand awareness with top-tier computer science students.
  • Contribute to the local community by providing mentorship to educate the next generation of computer scientists who will shape Utah’s future.
  • Give back to U Engineering.


Sponsor Requirements

Cost to Sponsor a Project

The cost to sponsor a Clinical Capstone Project is $15,000 for a team of 3 students, and $20,000 for a team of 4 students. These funds support a $2,000 scholarship for each team member, administrative costs to run the program, software and other resources that the project will require, and funding for Demo Day expenses.

Who Owns the Intellectual Property Generated by the Project?

The sponsoring organization will own any intellectual property generated by the project.

Will the Student Team Have to Sign a Non-Disclosure Agreement?

If the sponsoring company would like a non-disclosure agreement in place before the project begins, we can arrange that.

How Many Students Will Work on a Team?

Teams generally consist of 4 students. In the case where an additional student is added to the project, an additional $2,000 will be required for scholarship funds.

Do Students Choose Their Own Teams?

The Capstone faculty work to place top students who indicate interest in the project idea onto the clinical teams.

Still Have Questions?

Contact Sheri Carp in the Kahlert School of Computing at sheri@cs.utah.edu.

Check Out Some of Our Past Projects

Senior Capstone Demo Day 2023

Team: Worm World

Genetics researchers seek to determine how genes, the basic units of biological inheritance, influence the observable characteristics of organisms. The work done by geneticists includes cross-breeding (“crossing”) different strains of a species to obtain a target genetic profile. The current state-of-practice is to draw these cross trees and calculate offspring probabilities by hand, which can be error prone and time consuming. Our multi-platform desktop application allows researchers of the model organism C. Elegans to design, save, and share strain pedigrees that model the inheritance of relevant genes across generations according to statistical patterns. With this tool, researchers can streamline their experimental planning and data analysis, ultimately improving the efficiency and accuracy of their research.


Team: L3 Harris Clinic

All systems in a network are typically controlled via a centralized server. These servers will typically handle all connections and connect each caller to the person they intend to call. However, this approach has limitations in various high-stakes situations where you need to maintain communication without a single point of failure. To combat this, we have developed a distributed call management system that automatically meshes between users, without the need for a centralized server. This was achieved by creating, designing, and implementing a communication protocol for Linux and Windows platforms that uses multicast RTP to allow users to create and join calls on a network without requiring input from any centralized source.


Team: INL Clinic

Idaho National Laboratory (INL) has developed the All Hazards Analysis (AHA) framework in order to record information about the nation’s critical infrastructure and simulate the consequences of a disruption. The Spatial Enrichment Data Engine (SEDE) is a new and independent web service which will validate and assign accurate geospatial data to the infrastructure in INL’s AHA framework. We will provide non-spatial (e.g., address, zip code) and spatial information (latitude/longitude) by developing a forward and reverse geocoding application. We will also supply elevation data to INL to support flood simulations. Finally, we’ve developed a user interface to validate functionality and display geocoded results on a map.


Team: CaptionCall

Secret Keepers is a mobile journal application developed for both iOS and Android devices with the capabilities of capturing audio. Secret Keepers uses React Native for mobile app development, Google’s application programming interface (API) for emotion tracking, audio to text transcription, and data storage. There are two main purposes for Secret Keepers. The first purpose is to gather natural one-sided conversations from a multitude of different ages and ethnic groups. The information gathered will assist CaptionCall, a company who provides technology to people who are hard of hearing, with their speech-to-text predictive model. The second purpose is to be a fun and easy application that encourages people to speak to their devices.


Clinical Capstone Coordinator

Sheri Carp
Associate Director of Business Affairs
Kahlert School of Computing
University of Utah
sheri@cs.utah.edu

Faculty Lead for Clinical Capstone Program

Professor James de St. Germain
germain@cs.utah.edu


Information for New Graduates

Academic Advisors

Jill Wilson & Allen Hill (MS/PhD)
grad-advisors@cs.utah.edu

Leslie Wallwork & Sammie Riley (Master of Software Development)
msd-advisors@cs.utah.edu
801.581.7631

Vicki Jackson (Combined BS/MS)
vicki@cs.utah.edu
801.581.8224

Information

Don’t Forget to Eat – 

There are a lot of food options on or near campus for when you are stuck on campus all day.

  • The Union Center has a food court with the most options in one place: Panda Express, Jamba Juice, Burger Boi, Hive Pizza, etc.
  • The Warnock Engineering Building (WEB) has a small cafe next to the Catmull Gallery called “Starley Commons Cafe” that has coffee, pastries, meals, cold drinks, etc.
  • The William Brownning Building (WBB) has a small cafe called “Two Creek” that has coffee and pastries.
  • The Campus Store has snacks, cold drinks, and a Starbucks.

If you are having difficulty affording groceries, you can stop by the Feed U to pick up nonperishable items.

Connect with our GradSAC

What is it like to be a student in the Kahlert School of Computing? Do you have questions for our current students? The Graduate Student Advisory Committee maintains useful information. You may e-mail them at gradsac@cs.utah.edu or talk to our students on our Slack channel.

Setting up a Computer Account

Send email to CS Support (email). Then create a username 3-8 letters (common are last name, first name, first initial and last name, etc)

Payroll Process – 

Take a deep breath. The payroll process is a stressful time for all students, no matter what type of funding they are receiving. You are not alone.

If you need a Social Security number & have received a funding offer (fellowship, RA, or TA), contact the Grad Advisors and they can provide you a specific Social Security Letter that will enable you to get a Work Authorization form (from ISSS) and schedule an appointment with the Social Security Office.

Make sure to reach out to the Kahlert School of Computing accountants (accountants@cs.utah.edu) at the beginning of August so they can tell you exactly what documents they need in order for you get onto payroll.

It takes about 2 weeks to complete the payroll process entirely since all hires have to be approved by HR of the entire University of Utah.

Feeling Sick?

If you get sick or have a medical condition that needs attention, please go to the Madsen Health Center first. The co-pay(fee) is $10.00 and there is no additional charge for the visit. If it’s deemed necessary that you need to see an additional doctor, you will receive a referral, and other visits to medical professional involve additional charges.

For illnesses that occur when the center is closed, please go to Redwood Urgent Care. For EMERGENCIES, and for treatment when the Redwood Urgent Care center is closed, go to the nearest Emergency Room.

General Campus Links

Digital Resource Guide for New Students

International Center 

Graduate School

Price College of Engineering Counseling 

Community Resources

Commuter Services 

Campus Map

ID Card Works as bus, TRAX, and Front Runner train pass. Take ID card to Marriott Library and have activated as library card.

Career Services


Research Areas

Graduate Application for the Computer Science Degree: Specification of Research Areas of Interest

Graduate applicants to the Computer Science program will be asked to specify up to three areas of research interest in the online application form, from the list below. The primary topics of research currently being carried out in these areas by faculty members in the School of Computing are listed in the table below. Information about the areas of research of the faculty members may be found on the departmental faculty page and the departmental research page.

Research Areas Primary Research Topics
AI & Machine Learning Cognitive Systems; Explainable AI; ML & Fairness; ML & Systems; ML Theory, Physics-Informed ML; Representation Learning; Reinforcement Learning; Structured Learning & Prediction
Algorithms & Theory Approximation Algorithms; External Memory Algorithms; Graph Algorithms; Parameterized Algorithms and Complexity; Resource-Efficient Data Structures; Theoretical Cryptography
Computational Science Computational Biology; Computational Inverse Problems; High-Performance Scientific Computing; PDE Solvers
Computer Architecture Accelerators; Architecture-Codesign; Coherence Protocols; Hardware Security; Memory Systems; Microarchitecture Synthesis; VLSI
Computational Geometry & Topology Applied and Computational Topology; Computational Geometry; Geometric Data Analysis; High-dimensional Geometry; Topological Data Analysis
Computer Graphics Real-Time Rendering; Computer Animation; Physics-Based Rendering; Physics-Based Simulation; Geometric Modeling; GPU Algorithms; Ray Tracing Hardware
CS Education Ethics in CS Courses; Code Structure
Computer Networks Internet of Things; Mobile & Wireless Networks; Networks & Systems; Network Security & Reliability
Computer Vision Vision and AI; Visual Perception
Data Management Algorithms for Data Analytics; Data Discovery; Data Quality; Data Usability; Ethical/Responsible Data Management; Large-Scale Data Analysis
Formal Verification Protocol Verification; Verification of Concurrent Programs; Verification Tools
High-Performance Computing Accelerators; Cloud Computing; Compiler Optimization; Distributed Systems; High-Performance Scientific Computing; Parallel Computing; Scalable Systems
Human-Computer Interaction Computer Games; Personal Data; Social Computing; Ubiquitous Computing
Imaging Medical & Biological Image Analysis; Deep Learning for Image Analysis; Statistical Machine Learning for Image and Shape Analysis;  Scalable Methods and Architectures for Image Analysis; Shape Modeling & Analysis; Computational Anatomy and Geometric Statistics
Natural Language Processing Information Extraction; Interpretability; Interactivity & Analysis of Models; Learning for NLP; Multimodality; Natural Language Understanding (NLU); Semantics; Sentiment Analysis
Operating Systems Distributed Operating Systems; Distributed Key-Value Stores; Fast Datacenter Stacks; Secure OS
Programming Languages Compiler Optimization; Design & Implementation of Programming Languages; Software Testing; Trustworthy Systems Software
Robotics Autonomous Systems and Learning; Human-Robot Interaction; Medical Robotics; Motion Planning
Security & Privacy Cryptography; Mobile Security; Human Aspects of Security & Privacy; Software & System Security
Visualization Data Visualization; Scientific Visualization; Topological Data Analysis

Undergraduate Academic Program Overview

The University of Utah Kahlert School of Computing nationally-ranked program offers its undergraduates a rigorous blend of theory and practice to prepare them for the jobs of today and the challenges of tomorrow. Our students have opportunities to work with cutting-edge researchers, along with excellent access to Silicon Slopes and top-tier national tech companies. Set on a beautiful campus, students enjoy recreation in the surrounding mountains as well as urban Salt Lake City.

Degree options

Students in the Kahlert School of Computing can pursue degrees in computer science, data science, software development, computer engineering:

  • Computer Science encompasses the theory and discipline of solving computational problems. Computer scientists analyze and engineer the software, algorithms, computer systems, and theories that continue to advance the modern technological world. They work in a broad range of areas including artificial intelligence, security, graphics, robotics, operating systems, networking and communication.
  • Data Science focuses on the practice and theory of extracting useful knowledge, results, and understanding from raw data. Data scientists typically work with consumers and producers of data in order to analyze, manage, and augment large data sets or work in industries that require automated forms of decision making and analysis.
  • Software Development is the study of the principles, tools, and techniques for developing modern software. Software developers create the web, mobile, and desktop applications that we use every day. They typically work as full stack developers, writing and maintaining the secure front end and back end code that turns a specification into a real-world, functioning system.
  • Computer Engineering emphasizes the physical and hardware aspects of computing. Computer engineers design computer circuits, processors, and the electronic systems and devices that computers control. Computer engineers also design and develop the software to analyze and control sophisticated devices and machines.

Full degree requirements for each program can be found in the student handbook. Additionally, the Kahlert School of Computing offers a special games track in Entertainment Arts and Engineering, as well as a five year combined BS/MS program, which allows students to complete both degrees in about five years, by taking both undergraduate- and graduate-level courses in their senior year.

Benefits

Students achieving an undergraduate degree from the Kahlert School of Computing are very successful in the job market, as 92% of students secure full-time jobs before they graduate. Many internship opportunities and job offers are a result of the Kahlert School of Computing’s annual career fair.

The University of Utah is an R1 research university. What this means for undergraduate students is that many classes are taught by faculty who are active in research and experts in their fields. Additionally, there are opportunities for undergraduates to engage in cutting-edge research while at the University of Utah.

How to apply

Interested students should apply for admission to the University of Utah: https://admissions.utah.edu/apply/
Early action deadline: December 1, 2023
Merit scholarship consideration deadline: December 1, 2023 (Freshman Only)
PCE Department Scholarship deadline: February 1, 2024
Application deadline: April 1, 2023


BS Data Science

Undergraduate Data Science

Did you know… the University of Utah is home to the Utah Center for Data Science?

To learn more about becoming a member, research and mentoring, and upcoming events, visit:

Image opens in new tab


Data Science is the emerging field that manages and makes sense of data to solve important challenges in science, engineering, and society.

While a data science relies on technical skills from computing and mathematical modeling, the key to its success is the ability to choose among the techniques, interpret them, and connect them with the data domains.

Most of todays cutting edge work relies on the efficient and informed collection, management, and analysis of data. If you want to become a data scientist or work with one, the School of Computing offers several degree and certificate programs towards helping you learn the skills necessary to be at the center of these modern grand challenges.


Undergraduate Program

Bachelors of Science in Data Science

Additional information, flowcharts, and approved elective options for the major can be found by accessing the above link

School of Computing Undergraduate Tutoring Center

Undergraduate Certificates

Certificates in Data Science and Data Fluency

Additional resources and forms for those wishing to pursue either of the undergraduate certificates can be found by accessing the above link

Major Elective Evaluation Request

Undergraduate Data Science advising: DS-ugshelp@cs.utah.edu


Looking for graduate information? Visit the current graduate handbook to learn about the Data Management and Analysis track and our resource for the Data Science graduate certificate.

BS in Data Science

Analysis

We have created one of the first comprehensive Data Science bachelor’s degrees in the Mountain West.

This program will prepare individuals to develop and apply knowledge of basic computer science and software engineering sufficient to be able to build, modify, or use software tools for data analysis. These students will also learn fundamentals of data analysis and processing in order to be able to effectively, efficiently, and ethically make decisions based on the information within various data sources.

Graduates of the proposed program will fill a growing demand for data scientists and work in a variety of industries including health care, finance, and the internet. They will typically work with consumers of data in order to analyze, manage, and augment large data sets or work in industries that require automated forms of decision making and analysis. In situations that require large and sophisticated software development for data analysis, these graduates may work with or lead teams of computer scientists or software developers in a joint effort.

Looking for the Data Science or Fluency Undergraduate Certificates? Visit https://www.cs.utah.edu/undergraduate/data-science/#certificates for details and resources.

Jeff Photo

In recent years, Data Scientist is commonly listed as one of best jobs in the United States. For instance, a Forbes article from January 2018 based on the hiring website “Glassdoor.com” reports
“Data Scientist has been named the best job in America for three years running, with a median base salary of $110,000 and 4,524 job openings.” Related jobs “Analytics Manager,” “Data Engineer,” and “Data Analyst” rank 18, 33 and 38, respectively, on this list. Note that all of these jobs are listed as distinct from more traditional Computer Science jobs “Software Engineer,” “DevOps Engineer,” “Mobile Developer,” “Front End Engineer,” etc.

The Utah Economic Data Viewer does not include an explicit category for “data scientist,” with the closest being “Computer and Information Research Scientists.“ This is likely related also to a Computer Science degree, but likely includes data scientists. For this field, the annual median state-wide wages are $91,090 and there are expected 30 annual openings statewide and 600 in the United states. While the listing notes that many of these jobs expect a “Doctoral or professional degree,” the data scientist panel we hosted in August 2017 provided some insight into why an applicant with a BS in Data Science may be competitive. Many entry level jobs are labeled as “Data Engineer” and “Data Analyst” whereas jobs titled “Data Scientist” often expect some seniority and include some management component. At least among those on the panel, they mainly obtained this necessary experience on the job.

Undergraduate Data Certificates

Data Science Banner

We believe any student at the University of Utah wanting to incorporate data into their degree plans will be able to do so — regardless of major!

What is data science?

The worlds of science, engineering, and business are now reliant on data-driven analysis and decision making. Data Science is the 21st century discipline formalizing this process, and making enormous impacts in new scientific discoveries, engineering how the world works, and driving business decisions which power much of our economic growth. A data scientist is one who can weave a complete story with data, from its humble and messy beginnings, through its maturation via sophisticated analysis, and concluding with an explanation of its real-world impact.

According to a June 2021 Forbes article, “The U.S. Bureau of Labor Statistics sees strong growth for data science jobs skills in its prediction that the data science field will grow about 28% through 2026.”

Data is everywhere, and so are the opportunities with data in multiple fields!

The University of Utah offers two undergraduate certificates related to data science:

The Undergraduate Certificate in Data Science is meant for students seeking to learn the basics in data understanding, processing, and analysis, and was designed for those pursuing degrees in a STEM program. Calculus experience is assumed for this certificate.

The Undergraduate Certificate in Data Fluency is meant to provide students a basic understanding and exposure of areas within data, and the ability to relate these topics to their main focus of study.

Have questions? Email DS-ugshelp@cs.utah.edu for assistance.

Undergraduate Certificate Forms and Resources

The current electives approved to satisfy certificate requirements can be reviewed by accessing our online resource.

Need some help with your introductory programming courses? Visit our FREE tutoring center!

Express your Interest in one of our undergraduate certificates! This will allow us to keep track of, monitor, and advise your progress.

Think you have completed the requirements a data undergraduate certificates? Fill this out after you have enrolled in your final semester of courses.

Students, is there a data-rich U of U course you discovered, but it’s not on the pre-approved list? Complete this form to have it evaluated!

Faculty and staff, if you would like to have one of your department’s courses evaluated for the Data Science Bachelors or Certificate, or the Data Fluency Certificate, please submit this form.

Data Science FAQ

Data Center

Q: Can I double major in Computer Science and Data Science?
A: Yes. However, keep in mind, this would require completing 2 senior projects/theses.

Q: Can I apply for a BS/MS degree with the BS in Data Science, and the MS in Computer Science or Computing?
A: Yes. note that if one chooses the MS in Computer Science, then CS 6810, Computer Architecture, would be required. For that course, it is recommended to take Cs 3810, Computer Organization, during the BS portion of the degree. The MS in Computing does not require CS 6810, Computer Architecture.

Q: How do I apply for full major status (FMS) in Data Science?
A: The pre-major requirements and application are currently the same as those pursuing Computer Science. The application for Fall 2022 admission is now open! If you are ready to apply, please click here for access.

Q: Can I take MATH 1210 and MATH 1220, Calculus I and II, instead of the Engineering Calculus sequence, MATH 1310 and MATH 1320?
A: Yes. Engineering Calculus can be replaced with MATH 1210 and MATH 1220, however, you are strongly encouraged to complete MATH 2210**, Calculus III, in order to learn that missing material you would have covered in MATH 1320.

Students are recommended to take MATH 2270, Linear Algebra, as soon as possible because it is part of a sequence of important prerequisite chain, building upon each other. The MATH 1310 and 1320 sequence better prepares students for MATH 2270 and to enroll in it sooner, allowing students more flexibility in their timing to take other advanced data science courses.

** A recent update to the prerequisites of MATH 2270 allows students who earn a B or higher in MATH 1220 to enroll in the course without first completing MATH 2210. Those who do not meet this threshold will be required to succeed in Calculus III in order to enroll in Linear Algebra. There are no exceptions.

Student Photo

Q: Is there a Minor in Data Science?
A: There may be one in the future, but there are currently no concrete plans for which courses would constitute a minor. However, we do offer two different data-related undergraduate certificates, Data Science and Data Fluency. Learn more about these options and available resources by clicking here!

Q: Can I take Electives (either Data Analysis Breadth or Data Domain ones) other than those provided on the approved lists?
A: It is certainly possible! Those are the pre-approved courses, but there are potentially many more that would qualify. Students are able to submit their requests by submitting the form linked here.

The Data Analysis Breadth electives are meant to provide a broader picture of the array of techniques in data science.

The Data Domain electives are meant to expose students to a data rich domain (e.g., in Engineering, Science, Medicine, etc) where the other skills learned in the degree would be applicable. These courses may be billed as “technique” or “technology” courses in their own disciplines, but from the perspective of a data science student, the working through of the in depth application of those techniques in that domain will be the desired aspect. Indeed each domain often has its own specific data challenges, and being exposed and aware of these issues is an important outcome of taking such a course.

In both cases, the courses do not need to be a specific sequence within a single data or technique domain. They should suit the students interests and their overall educational and career plan.

Q: I cannot figure out how to register for the Data Wrangling course.
A: Currently, DS 2500 is a spring-only course. Make sure you are planning your semester schedules carefully with your School of Computing undergraduate advisor!

Q: Does the DS 3390 Ethics in Data Science course satisfy the Social/Behavioral Science (BF) requirement? If I already completed both of my BF courses, will I need to take another course to satisfy that requirement?
A: No, it does not. We had planned to try to allow this, but it was not possible. Make sure to complete at least 2 BF courses to satisfy this university general education requirement.

Q: My question was not asked/answered here. How can I ask for clarification?
A: If a policy is not explicitly stated here, or answered in this FAQ, but there is a relevant one for Computer Science, as listed in the handbook, then the DS policy will default to that one. This includes policies on Academic Misconduct, Non-Discrimination, and Sexual Misconduct — which conform to the University of Utah guidelines. The undergraduate handbook for Data Science is coming soon!

Please email DS-ugshelp@cs.utah.edu to contact the SOC undergraduate advisors or the Director of the Data Science Program with additional questions.


Tutoring

Tutoring Center

School of Computing | Undergraduate Tutoring Center | Monday – Friday | MEB 3145

The tutor helped me write the things I would use, rather than smacking me with a brick of text. It helped me feel an understanding of the concepts we went over.

Pre-Major Student, Spring 2021

My tutor is really good at explaining concepts in various ways and doesn’t just give the answers away, but helps you to come to the answer yourself… It was so beneficial and I’m feeling optimistic about my class again.

Pre-Major Student, Spring 2021

Need some help with your computing courses?

The School of Computing (SOC) offers assistance for the concepts learned in our introductory- and intermediate-level computing courses. Our tutors have gained Full Major Status in Computer Science and Computer Engineering and have experienced many of the new challenges you are encountering right now! Learn more about our tutors here

Our center is a FREE 1:1 resource to utilize in addition to your courses’ TA services and instructor office hours, with drop in availability every weekday! To view what courses we are currently covering — as well as additional campus resources — click here.

Our tutors are available to meet with students via drop-in hours in our tutoring center. Drop-In sessions will also be held via zoom, be sure to check for your tutors individual zoom link and tutoring hours.

Have questions about the tutoring center? Email ugrad-help@cs.utah.edu


Spring 2024 Information

Schedule: The tutoring center will open January 16th and close April 23rd.

The tutoring center is closed during University Closures and holidays –

Locations: MEB 3145

MEB 3145 HOURS OF OPERATION

MONDAY TUESDAY WEDNESDAY THURSDAY FRIDAY
11AM-7PM 8AM-5PM 10AM-7PM 8AM-6PM 9AM-5PM


Meet our Tutors

Student Photo

Hyrum Bailey

Major – Computer Engineering

Two of my favorite projects in CS 3500 are when we made a spreadsheet and a game. The game brought up a lot of little problems that I didn’t imagine would come up and it was awesome putting it all together.

I especially enjoyed 1400 and 1410. They were my first programming classes and I had great teachers in both of them. I love coding in general because it gives you the satisfaction of solving a problem.


Hyrum tutors: CS 1400, 1410, 1420, 2100, 2420, 3500, 3505, 3810, 4150 and COMP 1010, 1020

Hyrum’s Drop In Tutoring Zoom Link

Passcode: 208649

Below is Hyrum’s schedule


Student Photo

Toshi Mowery

Majors – Computer Science and Mathematics

Toshi is a CS Math double major who enjoys topics relating to algorithms and discrete math.

His video games of choice are currently Dota 2 and Magic the Gathering, but you can also find him playing the piano — everything from Beethoven to anime.

Favorite CS courses to tutor: CS 2100, 2420


Toshi tutors: CS 1400, 1410, 1420, 2100, 2420, 3500, 3505, 3810, 4150, and COMP 1010, 1020

Toshi’s Drop In Tutoring Zoom Link

Passcode: 580545

Below is Toshi’s schedule


Theo Kremer

Majors – Computer Science

Theo’s a passionate computer science tutor with a keen interest in full-stack development. He’s able to break down complex concepts into easily understandable terms. When not tutoring, he enjoys exploring new technologies, engaging in creative projects, and rock climbing

Favorite courses to tutor: CS2420 CS3500


Theo tutors: CS 1400, 1410, 1420, 2100, 2420, 3500, 3505, and 3810.

Theo’s Drop In Tutoring Zoom Link

Meeting ID: 727 0615 9455
Passcode: 3B0GhU

 

Below is Theo’s schedule


Aidan Bauer

Majors – Computer Science

Hi! I’m Aidan. I’m a sophomore CS major from New Hampshire. Outside of school I love to ski, climb and hike. Feel free to drop into the tutoring center during my hours and I am happy to help.


Aidan tutors: CS 1400, 1410, 1420, 2420, 2100, and 3500.

Aidan’s Drop In Tutoring Zoom Link

Below is Aidan’s schedule


Surbhi Saini

Majors – Computer Science

Hi everyone! I’m Surbhi and I’m originally from India with a passion for computer science because of its problem solving skills and I enjoy solving the challenges encountered while coding! I found CS 3500 very interesting and fun since the concepts in all assignments come together in the end as a working application. Outside of college, I love to travel, watch movies, play board games and also hang out with friends!


Surbhi Tutors: CS 1400, CS 1410, CS 1420, 3500 and CS 3505

Surbhi’s Drop In Tutoring Zoom Link

Below is Surbhi’s schedule


Emily Best

Majors – Computer Science

Hi! My name is Emily and I’m graduating with a BS in Computer Science this Spring! I like computer science for its problem-solving and widespread applications. Outside of studying, I also like to read, play the piano, hike, and ski 🙂

Besides the classes I tutor, if you have questions about resumes, interviews, or internships, feel free to ask me! I’ve had a few internships and would love to offer suggestions.



Emily tutors: CS 1400, 1410, 1420, 2100, 2420, 3130, 3500, 3505, 3810, 4150 and 4400.

Emily’s Drop In Tutoring Zoom Link

Below is Emily’s schedule


Additional Tutoring Resources

Learning Center 
Mathematics Student Center
Physics Tutoring Resources
Writing Centerboth lower- and upper-division writing assistance