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Data Science (M.A.S.)

Develop the skills to master the cutting-edge tools and techniques essential to become a leader in the rapidly growing big data analytics field.

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Master the Skills to Lead in Future-Forward Big Data Industries with ÐÓ°ÉÂÛ̳’s Master of Data Science

Data is everywhere and part of everything we do—and the data science landscape is constantly evolving. Professionals who are able to master big data and stay current with the most up-to-date trends in the field are vital to meet this moment. Prepare with skills and knowledge to lead in machine learning, deep learning, artificial intelligence, big data analytics, and data visualizations with ÐÓ°ÉÂÛ̳’s project-based Master of Data Science. By learning how to maximize modern tools such as Python, R, TensorFlow, and Hadoop and working on real-world projects with industry partners, you’ll develop in-demand, industry-relevant skills to take your career to the next level.

Program Overview

Develop expertise in machine learning, deep learning, big data analytics, and data visualization to by building a strong foundation in mathematics, programming, or statistics in ÐÓ°ÉÂÛ̳’s Master of Data Science. Through collaborative real-world projects with industry partners, you’ll build a network of connections and showcase your experience in cutting-edge, relevant data. Plus, you’ll do it on your schedule: you can take courses online, in-person, or via hybrid formats as part of a program offered on full-time, part-time, or self-paced schedules in order to work with your schedule.

Career Opportunities

Graduates of our master’s program in data science are prepared for a multitude of careers, such as:  

  • Data Scientist
  • Data Analyst
  • Machine Learning Engineer
Disclaimer for prospective students, please read.
The information provided is sourced from a third party, Lightcast, and is provided here for informational and educational purposes only. Please be advised that the inclusion of the Lightcast resource on this website does not imply endorsement by Illinois Institute of Technology (ÐÓ°ÉÂÛ̳), nor is it a guarantee of the accuracy of this information. ÐÓ°ÉÂÛ̳ makes no representation, warranty or guarantee, express or implied, that the information presented herein is reflective of the outcomes you can expect if you enroll in or graduate from an ÐÓ°ÉÂÛ̳ program. ÐÓ°ÉÂÛ̳ expressly disclaims any liability regarding Lightcast, or in connection with any actual or potential employment opportunity stemming from information on this site and you hereby irrevocably waive any claim(s) against the ÐÓ°ÉÂÛ̳ for the same. Your use of this web page is an acknowledgement of your understanding and acceptance of the terms and conditions set forth herein. You are encouraged to conduct your own thorough research into job opportunities and outcomes in your field of study.

Here are some courses that are among our students’ favorites:

CS 577 Deep Learning and Neural Network You’ll explore advanced deep learning techniques such as neural networks, CNNs, and RNNs by utilizing modern tools such as TensorFlow and PyTorch to build models for image recognition and natural language processing in this course.  

CS 584/MATH 569 Machine Learning/Statistical Learning In this course, you’ll master machine learning algorithms and build predictive models using real-world data.

CSP 554 Big Data Technology You’ll learn to handle massive data sets using real-world tools such Hadoop and Spark, and cloud platforms such as Amazon Web Services and Google Cloud in this course. 

You must complete the ÐÓ°ÉÂÛ̳ graduate application, regardless of which graduate program you wish to pursue. Visit our admission website to learn more about what information and documents you need to apply.    

Please note that each college and individual programs may have additional requirements to apply. Please contact the Department of Computer Science at computerscience@illinoistech.edu with any questions. 

TOEFL/PTE/IELTS scores may be required for some applicants.

Tuition and Fees

Learn more about the university’s general tuition and fees, visit the Student Accounting website.

Featured Faculty

Yuhan Ding

Yuhan Ding

Associate Teaching Professor of Applied Mathematics Program Director, Master of Data Science
Ioan Raicu

Ioan Raicu

Professor of Computer Science Associate Program Director Master of Data Science
Mustafa Bilgic

Mustafa Bilgic

Chair, Department of Computer Science Professor of Computer Science Program Director, Master of Artificial Intelligence
Sonja Petrovic

Sonja Petrović

Professor of Applied Mathematics
Gady Agam

Gady Agam

Associate Professor of Computer Science
Maggie Cheng

Maggie Cheng

Professor of Applied Mathematics Director, Center for Interdisciplinary Scientific Computation

Real-World Impact

Megha.L.DSAlumnea
Data Scientist, Capgemini

Megha Lokanadham says the Data Science program at ÐÓ°ÉÂÛ̳ covers all the topics that students need to be ready for a career in the field

Megha Lokanadham (M.A.S. DATA SCIENCE '18)
Utkarsh Khanna
Software Developer, Google

Lessons learned through faculty mentoring impact Utkarsh Khanna’s approach to workplace projects.

Utkarsh Khanna (M.A.S. Data Science ’16)
Photo of Mamta Kanvinde
Data Analytics Developer, GreenerU

Mamta Kanvinde still reviews the notes she took during class while earning her Master of Data Science degree at ÐÓ°ÉÂÛ̳.

Mamta Kanvinde (M.A.S. Data Science ’16)
Vinod Rao DS Alumnus
Data Scientist, Eli Lily & Co.

Vinod Rao says the capstone practicum project in ÐÓ°ÉÂÛ̳’s Data Science program showed him how to apply data to solve a real-world problem.

Vinod Rao (M.A.S. DATA SCIENCE '18)
Ying Wu
IT Analyst, Blue Cross Blue Shield Association

As an IT analyst, Ying Wu uses tools and technologies such as machine learning, statistics, and data visualization, all of which she studied in the data science program.

Ying Wu (M.A.S. DATA SCIENCE ’17)
MKGaddamDSAlumnus
Senior Systems Analyst, Blue Cross/Blue Shield

Manoj Kumar Gaddam credits the techniques taught in ÐÓ°ÉÂÛ̳’s Data Science program prepared him for a professional setting

Manoj Kumar Gaddam (M.A.S. DATA SCIENCE '18)

Hands-On Experience

Take advantage of the opportunity to work on a real-world, data driven problem through a distinct practicum. This experiential component complements your coursework in the data science curriculum by working in small teams of students with Chicago-area companies such as Accenture, Orbitz Labs, Siemens, and Aegis. Weekly meetings with a faculty instructor and a partner representative ensure project goals are being met and delivered on time.

Get In Touch

To learn more about the program, please contact Yuhan Ding, director of the Master of Data Science, at yding2@illinoistech.edu.