Online M.S. in Data Science & Engineering

About

The online M.S. in Data Science and Engineering trains students to manage, analyze, and visualize large and complex data sets. The program accommodates students from various academic backgrounds and offers specializations in different domains. The multiple paths to graduation make the new program highly flexible in meeting individual student needs.

Program Learning Outcomes

Graduates of this program will learn:

  • Different data sources, acquisition processes, types, quality, and cleaning methods.
  • The issues affecting the efficient processing, representation, storage, management, and retrieval of large amounts of data.
  • How to leverage modern computational infrastructures and software tools to perform large-scale data analysis and machine learning.
  • Standard analytical tools, their methods, their practical use, and the strengths and limitations of each.
  • The skills to effectively explore and present data to different audiences through visual and multimodal methods.
  • Strategies for data security, curation, and preservation.
  • The ethical issues, risks, and responsibilities related to data science.

Admissions

We have rolling admissions, meaning you can apply and be accepted at any time. The admission evaluation process begins once we’ve received all of your application materials.

  • A bachelor’s degree from an accredited college/university with a minimum GPA of 3.0 on a 4.0 scale
    A GPA lower than 3.0 will be considered on a case-by-case basis
  • One college-level statistics course
    Applicants without this requirement may take an approved college statistics course before or as part of conditional or provisional admission.

Before you apply, please review the application instructions. When you’re ready to apply, please submit the following:

  • An online application
  • Current résumé or CV
  • Official academic transcripts from all institutions attended
  • An essay describing your motivations, life experiences, and ability to succeed in a graduate program

Careers

The private, public, and research sectors rely heavily on data science and engineering to analyze and translate massive, complex, heterogeneous, and dynamic data into manageable forms, creating new information and providing insights to better understand phenomena and guide decision-making. Businesses, governments, and academic institutions throughout Maine and beyond increasingly need a workforce well trained in these skills.

Data Scientist

According to the U.S. Bureau of Labor Statistics (BLS), employment of data scientists is projected to grow 35% from 2022 to 2032, faster than the average for all occupations. About 17,000 openings for data scientists are projected each year, on average, over the decade.

Median Salary: $108,020

Curriculum

Numerous course paths exist for earning the M.S. in Data Science and Engineering. Course selection varies based on each student’s background and interests, and whether prerequisites have been met through previous coursework.

Throughout your coursework, you’ll work closely with a faculty advisor to ensure your program of study best fits you and your goals.

The following courses are required (30 credits):

At least one course that includes substantial practical experience is recommended. Examples of courses are:

  • DSE 589: Data Science and Engineering Graduate Project (3 credits)
  • DSE 590: Data Science and Engineering Internship (3 credits)
Person pointing to computer

At a Glance

UMaineOnline

Maine College of Engineering & Computing


Degree Level

Master

Degree Earned

Master of Science in Data Science & Engineering

Application Deadline

Rolling Admissions

Mode of Study

Online

Number of Credits

30 Credits

UMaineOnline

Maine College of Engineering & Computing


Degree Level

Master

Degree Earned

Master of Science in Data Science & Engineering

Application Deadline

Rolling Admissions

Mode of Study

Online

Number of Credits

30 Credits

Cost Per Credit Hour

E-Rate

$651

Photo of Kimberly Lai

Contact

Kimberly Lai, M.A.

UMaineOnline Advisor

umaine.edu/online

P

207.581.8041