Applied Computing

MSE with Applied Computing Emphasis


The objective of the Applied Computing emphasis in MSE program is to offer an opportunity for students who have completed a bachelor’s degree to gain the necessary computing knowledge and skills for a career in applied computing or enhancing the students’ computing ability for working in their own field. The Objective of this emphasis is not to train computer or software engineers. This program also offers a path to a generic MS-level data science program for students without a computer or software engineering degree.

Job Prospect

Upon successful completion of the program, students are expected to obtain either entry level data computing, data science, data analytics, or data management jobs, or have the ability to secure data-related jobs in their own discipline.

Program of Study

The program of study of is consisted of 30 units (10 courses), typically completed in 2 academic years (4 semesters). Typically, students are taking 3 courses per semester. Some courses in the program include Data Technology (Introduction to R), Database, Data Inference, Data Visualization, Machine Learning Applications, and Project course. Students will also have a chance to take a number of elective courses (such as user experience design or web programming), based on their career path and future goals. Upon completion of degree, students will get a MS in Engineering.

The following is the tentative plan of study for the MS in Engineering with Applied Computing emphasis. Students may follow a different plan including different courses with the approval of the program advisor.


 (can be waived by
 proof of competency)

 Basic Statistics
 Python programming
 Data Structures and Algorithms

 Year One

 Semester One:

 ENGR 200W* - Engineering Reports and Graduate Research
 ENGR 201 - Engineering Analysis
 ENGR 122 - Data Technology (using R)

 Semester Two:

 ENGR202 - Systems Engineering
 Data Visualization/Integration
 Data Inference

 Taking ENGR200W is for meeting the GWAR requirement. For more information   visit

 Year Two

 Semester One:

 ENGR281 (1-unit project)
 Database Applied Machine Learning
 Elective 1

 Semester Two

 ENGR298 (2-units project)
 Elective 2


Admission Requirements

In addition to the general requirements for the MSE program (see for more details), prospect students are expected to have a good knowledge of discrete mathematics, basic statistics, Python programming, and data structures and algorithms; otherwise students will be required to take up to 3 ramp courses to acquire these subjects before starting the MSE program. Students with an undergraduate degree in STEM typically have the basic knowledge of mathematics and statistics and may be required to take only 2 ramp courses or fewer (based on their Python and data structures knowledge) while students with an undergraduate degree in social science or liberal arts may be required to take mathematics and statistics courses as well. At the time of admission, required prerequisites will be specified for each applicant.