Master of Science in Engineering With Certificate of Specialization in Data Science Engineering

University of California - Los Angeles

Issuing School Samueli School Of Engineering
Description from the School

The exponential growth of data generated by machines and humans present unprecedented challenges and opportunities. From the analysis of this “big data”, businesses can learn key insights about their customers to make informed business decisions. Scientists can discover previously unknown patterns hidden deep inside the mountains of data. In this program, students will learn key techniques used to design and build big data systems and gain familiarity with data-mining and machine-learning techniques that are the foundations behind successful information search, predictive analysis, smart personalization, and many other technology-based solutions to important problems in business and science.

In-State Cost $36,000
Out-of-State Cost $36,000
Delivery Model Fully Online
Completion Time 27 - 36 months
Diploma Different? No
Application Deadline 1 Dec 1, 2021
Application Deadline 2 Sep 20, 2021
Alumni Companies
Exam Required GRE
Transfer Available No
Credits Needed to Complete 36
College Funded Aid No
Admission Requirements

The minimum requirements for admission to graduate study at UCLA are:

  • A bachelor’s degree in an engineering discipline, mathematics, or physics (NO EXCEPTIONS)
  • A GPA of 3.0 in the last two years of undergraduate coursework
  • GRE test scores (can be waived for well qualified applicants–please e-mail to inquire)
  • TOEFL/IELTS (Required for international applicants)

In addition to the requirements above, the MS Engineering Online Program requires the following:

  • A degree in engineering, computer science, mathematics, physics, chemistry, or the equivalent
  • A GPA above the UCLA minimum threshold
  • Alternatively, if your GPA is very close to the UCLA threshold, please provide:
  • Strong GRE test scores
  • Outstanding letters of recommendation addressing your work experience in the area
  • Exceptional grades in graduate courses within the chosen area of study (A- or better)

Application Checklist

  • Submit official transcripts: Order an official transcript to be delivered via mail OR by electronic submission (e-transcript). International applicants: please click here to read additional information on submitting international transcripts.
  • Please note: Transcripts that are uploaded to the application portal are not considered official. In order to begin the review process, an official transcript must be received. [If you completed your undergraduate degree at UCLA, please notify us via e-mail with your UID as we can pull your transcript internally]. Once official transcripts are received, they cannot be returned to the applicant.
  • Mailing address: UCLA Samueli School of Engineering, MS ENGR Online Program: 4732 Boelter Hall, Box 951601, Los Angeles, CA 90095-1601
  • Electronic delivery: (must be sent from the institution, not by the student)
  • GRE Scores (school code is 9655). If this requirement has been waived, you may bypass this section on the online application.
  • Three letters of recommendation: Individuals may be academic and/or professional.
  • Statement of Purpose: Describe your purpose in applying for graduate study. In particular, describe the relationship between your chosen area of study and your current or future employment. Include any additional information that may aid in the evaluation of your preparation for graduate study at UCLA.
  • Personal History Statement (required as of 8/2019)

Degree Requirements:

At least nine courses are required (36 Units).

A minimum of five courses must be taken at the graduate level (excluding ENGR 299 Capstone Project course).

Students must meet the Comprehensive Exam Requirement (Please see comprehensive requirements below)

Core courses in Data Science Engineering (Select four courses from the list below)

COM SCI 143 Database Systems COM SCI 249 Current Topics in Data Structures OR EC ENGR 205A Matrix Analysis for Scientists and Engineers COM SCI 249 Big Data Analytics (Winter) OR EC ENGR 219 Large-Scale Data Mining: Models and Algorithms COM SCI 260 Machine Learning Algorithms EC ENGR 232E: Large-Scale Social and Complex Networks: Design and Algorithms COM SCI 262A: Learning and Reasoning with Bayesian Networks

As long as you take FOUR core courses, the remaining courses may be chosen from the list of recommended electives below (or you may choose to take other core courses as electives).

Effective Fall 2018: While students are encouraged to take electives within their major, a maximum of two courses may be taken outside Data Science as long as they are offered through the MSOL Program. (This will also apply to students who were admitted prior to Fall 2018).

Recommended electives for Data Science:

EC ENGR 131A Probability and Statistics EC ENGR M214A Digital Speech Processing EC ENGR 214B Advanced Topics in Speech Processing EC ENGR 235A Mathematical Foundations of Data Storage Systems COM SCI 246 Web Information Systems

Comprehensive Exam Requirement:

Students can meet the Comprehensive Exam Requirement in two ways: Choose (1 option below)

Option 1:

Take and Pass ENGR 299 Capstone Project course.

Option 2:

Take and pass three written exams for three different graduate level courses within the student’s area of specialization. The written exams are held concurrently with the final exam of the graduate level courses. Students may select which exams they would like to count towards the Comprehensive Exam requirement.


A maximum of (2) elective courses may be taken outside Data Science Engineering (i.e. other MSOL courses in Mechanical Engineering, Systems Engineering, Electrical Engineering, etc.)

Thesis Plan:



Students are expected to complete the degree within two academic years and one quarter, including two summer sessions. The maximum time allowed in this program is three academic years (nine quarters), excluding summer sessions.

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