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DISCOVER THE PATTERNS IN RAW DATA BY ANALYZING AND MANIPULATING DATA SETS. BECOME A COMMANDER OF INFORMATION.

Data Science (DS)

da·ta sci·ence

The extraction of actionable knowledge from rich and varied datasets to quantify and address the pressing concerns of a modern society.

Also Known As: Data Scientist, Software Engineer, Software Developer, Statistician, Machine Learning Scientists, Business Analytic Practitioners, Software Programming Analysts, Digital Analytic Consultant, Quality Analyst, +10,000 more

A stylized black and white image of a man looking up with a circuitboard outline layered over his face

WHY DS AT MICHIGAN?

  • No. 6

    institutional ranking in CS at CSrankings.org

  • 2015

    First offered, DS is a new major designed with input from leading alumni in the field.

  • 2

    colleges, joint program with Statistics in LSA

Technical rigor and relevance

Unravel key answers in the biggest data sets

Graduates highly sought in a field of rapid growth

A professor points to a screen and smiles as a group of students look on

What do Data Science Engineers do?

We are a new class of experts who extract actionable knowledge from rich, varied, and large datasets in order to find new associations that provide insight into current trends and big challenges. Using data that includes text, audio, video, and streaming and social data, we help to make discoveries in areas such as precision medicine, sustainability, space exploration, economics, and intelligent systems. We like big challenges!

APPLICATIONS

  • Biological Sciences

    Help to understand the natural order through bioinformatics, biostatistics, and computational biology. Investigate protein chemistry, genomics, systems biology, bioengineering, and environmental sciences.

  • Business and Industry

    Develop techniques for data collection, differentiation, and personalization, and intelligent systems that allow your company to offer more competitive, more calibrated, and better targeted offerings.

  • Government

    Uncover trends and make connections in data that can shed new insight on matters of policy or increase the efficiency and effectiveness of government operations.

  • Precision Health

    Collect and analyze data on individuals, populations, and environments that can be used to develop targeted and intelligent care regimes for patients.

  • Security

    Collect and analyze data from multiple sources that can reduce security risks, from video and physical proximity data through digital fingerprints. Develop defend against intelligent agents, botnets, and hackers.

  • Social Networks

    Collect and analyze data from user habits, preferences, devices, locations and interactions to develop more personalized and relevant experiences.

  • Sustainability

    Develop solutions that allow enterprises to minimize their environmental footprint through supply chain management, natural resource management, carbon reduction strategies, distribution strategies, and health and safety initiatives.

  • Transportation

    Develop smarter transportation systems that use data from vehicles, pedestrians, and fixed locations along with data about why transport is needed to create more efficient and sustainable solutions.

  • Areas in which a student, through the use of technical and free electives and extracurricular activities, could apply their major.

Areas in which a student, through the use of technical and free electives and extracurricular activities, could apply their major.

Graduate receiving hood during ceremony

Sequential Undergraduate/Graduate Studies Program (SUGS)

Complete your bachelor’s and master’s degrees in only five years with SUGS by taking some graduate-level classes during your undergraduate years, so you can save yourself one semester and complete the masters with only two additional semesters.

Learn More

Sample Course List

First-Year

First-Year

  • Fall Semester
    • CoE Core Calculus I (Math 115)
    • CoE Core Engineering 101
    • CoE Core Chemistry (125/126 and 130 or 210 and 211)
    • Elective Intellectual Breadth
  • Winter Semester
    • CoE Core Calculus II (Math 116)
    • CoE Core Engineering 100
    • CoE Core Physics (140 and 141)
    • Elective Intellectual Breadth

Sophomore Year

Sophomore Year

  • Fall Semester
    • CoE Core Physics (240 and 241)
    • Major Requirement Discrete Mathematics (EECS 203)
    • Major Requirement Programming & Elementary Data Structures (EECS 280)
    • Elective General Elective
  • Winter Semester
    • CoE Core Calculus III (Math 215)
    • Major Requirement Flexible Technical Elective
    • Major Requirement Data Structures and Algorithms (EECS 281)
    • Elective Intellectual Breadth

Junior Year

Junior Year

  • Fall Semester
    • CoE Core Linear Algebra (Math 217 or 214)
    • Major Requirement Probabability and Statistics (STATS 412)
    • Major Requirement Machine Learning (EECS 445) or Data Mining (STATS 415)
    • Elective Intellectual Breadth
  • Winter Semester
    • Major Requirement Applied Regression Analysis (STATS 413)
    • Major Requirement Databases & Applications (EECS 484 or 485)
    • Major Requirement Technical Communication (TCHNCLCM 300)
    • Major Requirement Flexible Technical Elective
    • Elective General Electives

Senior Year

Senior Year

  • Fall Semester
    • Major Requirement Major Design Experience Professionalism (EECS 496)
    • Major Requirement 400-Level Technical Communication
    • Major Requirement Data Science Applications Elective
    • Major Requirement Advanced Data Science Technical Elective
    • Major Requirement Flexible Technical Elective
  • Winter Semester
    • Major Requirement Data Science Capstone Course
    • Major Requirement Advanced Data Science Technical Elective
    • Elective General Elective
    • Elective General Elective

Individualized schedules will be made by students in consultation with an advisor who will tailor their classes to better fit the student's needs.

Practice Your Purpose

Apply the skills you are learning in class to the real world.

Student Design Teams

A2 Data Drive Logo
A2 Data Dive
An aerial view of students with laptops gathered around a table
Michigan Hackers
M Sail Logo
MSAIL - Michigan Student Artificial Intelligence Laboratory
A drone with 4 propellers floats in the air with a pyramid shaped center with a white box on tip and wires sticking out
MAAV - Michigan Autonomous Aerial Vehicles
A student races an all-terrain baja car with enormous wheels on a dirt track with mountains in the background.
Michigan Baja Racing
MDST Logo
MDST - Michigan Data Science Team
An electric racecar labeled with a large “Michigan” with a student driver wearing a full-face motorcycle helmet
Michigan Electric Racing
4 students wearing MRover shirts smile while carrying the rover, a machine platform with 4 tires and a robotic arm.
MRover - Michigan Mars Rover
2 team members wipe the completed maize and blue solar car. The car has a sleek design and half covered in solar panels.
Solar Car Team
A small vessel made up of two boxes sits in the NERS Fountain. The bottom box has a painted shark face
UM::Autonomy - Autonomous Boat
Members of Hyperloop pose for a photo in the North Campus Grove
Michigan Hyperloop
Students For Exploration And Development of Space
Students for the Exploration and Development of Space
A student in a full-face motorcycle helmet sits nearly horizontally as he rides the maize electric motorcycle named “Chronos”
SPARK - Electric Racing
A woman atop a roof wearing a hard hat and holding a power tool in front of a set of solar panels.
Grid Alternatives
Masa Logo
MASA - Michigan Aeronautical Science Association

Professional Development

Arbor Hacks Logo
ArborHacks
GEECS Logo
Girls in EECS
Code M Logo
Code-M
HKN Logo
Eta Kappa Nu - Honor Society
IEEE Logo
IEEE - Institute for Electrical and Electronics Engineers

Research

Laura Balzano headshot
Laura Balzano: Improve Machine Learning
READ MORE
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Alfred Hero & H.V. Jagadish: Michigan Institute for Data Science
READ MORE
Rada Mihalcea headshot
Rada Mihalcea: Language and Information Technologies Group
READ MORE
Jenna Wiens headshot
Jenna Wiens: Preventing Deadly Hospital Infections
READ MORE
Walter S. Lasecki headshot
Walter Lasecki: Crowds + Machines Lab
READ MORE
H V Jagadish headshot
Mike Cafarella, HV Jagadish & Barzan Mozafari: Database Research Group
READ MORE

Alumni Biographies

Each of these alumni are real people who were once in your shoes, deciding a major. Explore their path and how a Michigan education set their life in motion.

  • Usama Fayyad headshot
    • Usama Fayyad
    • Open Insights
  • Allie Cell headshot
    • Allie Cell
    • Shift
  • Headshot of Dev Goyal
    • Dev Goyal
    • HEALTH [at] SCALE Technologies
Usama Fayyad headshot

    Usama Fayyad

    Open Insights

Allie Cell headshot

    Allie Cell

    Shift

Headshot of Dev Goyal

    Dev Goyal

    HEALTH [at] SCALE Technologies

Not sure what major to choose?

Tap into our network of 85k+ engineering alumni. Do you have questions you’d like answered? Our alumni are always eager to talk about engineering.
(Current and admitted UM students only.)

Speak to an Alum
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Industries & Occupations

  • Software Industry
  • Federal Government
  • Internet-based companies
  • On-demand service companies
  • Business Consulting and Management
  • Financial Institutions
  • Data Analysis
The aerial view of an intersection in Ann Arbor with lights blurring as the cars speed through

Companies

  • Amazon
  • Apple
  • Central Data Systems
  • Bloomberg
  • BMW Technology Corporation
  • Cisco Systems
  • Citi
  • Coding It Forward
  • Facebook
  • Ford Motor Company
  • Geomagical Labs
  • Google
  • Hewlett Packard Enterprise
  • Hulu
  • IBM
  • JP Morgan Chase
  • Lockheed Martin
  • Microsoft
  • Motorola Solutions
  • National Instruments
  • Nest Labs, Inc.
  • OracleSprint
  • Tinder
  • Toyota
  • Twilio

Find salary information at the Bureau of Labor Statistics

LEARN MORE

LEARN MORE

Usama Fayyad headshot

Usama Fayyad

  • Open Insights
  • Chairman & CEO

University of Michigan, BSE Electrical Engineering
University of Michigan, BSE Computer Science
University of Michigan, MSE Computer Science
University of Michigan, Ph.D. Computer Science & Engineering, 1991
University of Michigan, M.Sc. Mathematics, 1989
Career Summary

Usama founded Open Insights as a technology and consulting firm to enable enterprises to get value from data, optimize or create new business models based on the new evolving economy of interactions through BigData strategy, new business models on data assets, and data science, AI/ML solutions. Usama is also Co-Founder & CTO at OODA Health, Inc a company aiming to liberate the healthcare system from administrative waste by leveraging AI/automation to create real-time/retail-like experience in payments in healthcare.

Usama previously served as Global Chief Data Officer & Group Managing Director at Barclays Bank in London, after launching the largest tech startup accelerator in MENA following his appointment as Executive Chairman of Oasis500 in Jordan by King Abdullah II. He was the first person to hold the Chief Data Officer title when Yahoo! acquired his second startup. At Yahoo! he built the Strategic Data Solutions group and founded Yahoo! Research Labs, where much of the early work on BigData made it to open source and led to Hadoop and other open-source contributions. He has held leadership roles at Microsoft and founded the Machine Learning Systems group at NASA’s Jet Propulsion Laboratory, where his work on machine learning resulted in the top Excellence in Research award from Caltech, and a U.S. Government medal from NASA.

Usama has published over 100 technical articles on data mining, data science, AI/ML, and databases. He holds over 30 patents and is a Fellow of both the AAAI and the ACM. He has edited two influential books on data mining/data science and served as editor-in-chief on two key industry journals. He is an active angel investor and advisor in many early-stage tech startups across the U.S., Europe and the Middle East.

Career Timeline
  • Open Insights
  • OODA Health, Inc.
  • Microsoft
  • NASA’s Jet Propulsion Lab
  • Yahoo!
  • Blue Kangaroo Corp
  • Oasis500
  • Barclays Bank
  • DMX Group
  • digiMine Inc.
  • Criteo
  • Invensense
  • Exelate
  • RapidMiner
  • Stella.AI
  • Virsec
  • Silniva
  • Abe.AI
  • NetSeer
  • Choicestream
  • Medio
  • Data Science Institute at Imperial College
  • AAI at UTS
  • University of Michigan College of Engineering National Advisory Board
  • Board Advisory Committee to Nationwide Building Society in the UK
  • WEF Global Center for Cybersecurity.
Advice to Students

Find your passion, and only work in areas where you are passionate about. Excellence will follow naturally. I enjoy working more than any other activity, except time with my kids. Your training in engineering at Michigan is a tremendous asset. Stay fresh, stay current. Change jobs as soon as you find yourself in your comfort zone – life truly begins outside your comfort zone.

I find a deeper understanding of history can really help humanity avoid repeating the mistakes of the past – unfortunately, most people get their history from propaganda and not deeper research. For example, most people do not understand the significance of the contributions of the Founding Fathers of the U.S. – these guys including the deepest thinkers, philosophers, scientists, and entrepreneurs of their times. I love that Declaration of Independence reads like a mathematical treatise: we hold these facts to be self-evident (axioms) and here is what follows.

What do you like to do outside of work?

I enjoy chess, swimming, reading books, great shows, and sleep when I can get it…

Allie Cell headshot

Allie Cell

  • Shift
  • Data Analyst

University of Michigan, BSE Data Science Engineering '18
Career Summary

I’ve only been at Shift (and out of college!) for just over a year, but I do love my job and am excited for where my career is going. I was hired as a Data Analyst — this means different things at different companies, but I work on a combination of high-impact business and product analyses and modeling work, primarily in python and SQL. One of the main things that I wanted in a job was to work with interesting data: as long as you’re solving complex problems with cool data, there’s going to be exciting work to get done. My company is in the used car space — pricing cars so we can acquire them, and also sell them, and also make money on them; finding buyers for cars in a marketplace; and defining and then getting the best inventory for our platform are some of the areas that I’ve worked on.

One project I’m finishing up right now involves dynamically adjusting how much we offer to pay for cars based off of how badly our inventory needs that car by looking at things like how much interest similar cars we have in inventory are getting. I love working at a start-up so that I’m able to have ownership in big projects that span multiple disciplines while learning from super talented coworkers, and that’s helping me get more knowledgeable in areas of data science that I’m weaker in. Having that ownership also means that communication and business sense and softer skills are really important, and that’s something I really like; in an ideal world, I’d continue to be involved with super high-impact data work as my career progresses, but also increasingly integral in the business decision-making processes. Other people in data science might instead want to specialize within data science (in areas like natural language processing or computer vision), but a degree in data science is a great stepping stone to either.

Reflection on Time Spent at U-M

During my time at Michigan, a lot of the data science curriculum was elective-based; this can allow you to start shaping your career by choosing to specialize in statistics or machine learning.

Advice to Students

Getting real data project experience is super valuable, so studying data science at a school with as many resources and opportunities as the University of Michigan (including the Michigan Data Science Team, Michigan Sports Analytics Society, Multidisciplinary Design Projects, research, data hackathons, etc.) is ideal.

Getting a job with the title of data scientist without an advanced degree can be hard, and data science as a field is constantly evolving. Be prepared to complement your education after graduating, which could be by attending conferences or taking online courses. Roles within data science vary widely — some are just analytics, some just machine learning, some do deep learning; I’d recommend either trying to figure out what aspects are your favorite (or least favorite) in college and then looking for jobs true to that, or to look at positions (maybe at start-ups!) that allow you to work on a range of disciplines, even if the title isn’t Data Scientist.

Headshot of Dev Goyal

Dev Goyal

  • HEALTH [at] SCALE Technologies
  • Lead Machine Learning Software Engineer

National University of Singapore, BE Mechanical Engineering, 2013
University of Michigan, MS Computer Science and Engineering, 2015
University of Michigan, PhD Candidate (not completed), Computer Science and Engineering 2017
Career Summary

At U-M, I took advanced graduate classes related to machine learning and AI. The faculty’s specialized knowledge about the practical applications of the techniques taught in these classes was especially helpful when applying for internships. I was able to get practical experience through class projects, which I eventually converted to longer term research projects. I met one of my PhD advisors in an EECS 598 class (Data Science in Medicine with Prof. Zeeshan Syed; I was co-advised by Prof. Jenna Wiens), and started my PhD as a result of the class. Eventually, I joined my advisor’s startup in Silicon Valley to work on problems related to healthcare. Aside from leveraging my technical training in machine learning and coding at university to built state-of-the-art healthcare solutions using machine learning, I’ve also leveraged out strong alumni network to recruit fresh U-M graduates to grow our ranks.

Reflection on Time Spent at U-M

I love coffee in Ann Arbor (Comet, Roos Roast), the fall leaves (biking to Dexter to get doughnuts and cider) and the summer festival. Not a big fan of the winter slush and April/May snow. EECS 545 and 586 gave me lots of grief (and late nights), but also were some of my happiest days in school. I especially enjoyed teaching ENGR 151 — it was a great way to have meaningful impact on freshmen eager to absorb as much as knowledge as possible 🙂 My university days were some of my happiest, and I hope everyone can enjoy them to the fullest!

Advice to Students

I recommend trying as many classes/projects/orgs as possible to really understand your likes and dislikes — this is your best opportunity to do so!

 

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