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Dual Degree in MME and Engineering Data Science

Rationale for the Program

Graduate students with a keen interest in both Mechanical Engineering and Engineering Data Science have the opportunity to pursue a dual degree program that strategically integrates courses from both disciplines. This innovative Dual Mechanical Engineering/Data Science Master's degree program enables students to earn both a Master in Mechanical Engineering (MME) degree and a Master of Science in Engineering Data Science (MSEDS) degree by completing forty-five (45) credit hours of relevant graduate coursework.

The required coursework includes:

  • Fifteen (15) credit hours of Mechanical Engineering courses
  • Fifteen (15) credit hours of Engineering Data Science courses
  • Fifteen (15) credit hours of shared coursework spanning both disciplines

The program's efficiency comes from its integrated curriculum, enabling students to satisfy the core requirements for both degrees through shared coursework. Compared to pursuing each degree separately with a total of sixty (60) credit hours, this dual-degree structure reduces redundancy by incorporating cross-listed or equivalent courses. Additionally, students follow a cohesive academic plan where interdisciplinary coursework reinforces key concepts in both fields. This structure equips students with interdisciplinary skills applicable to both traditional mechanical engineering and data science roles. The program is structured to optimize course availability and enable students to complete their degrees within a reasonable timeframe.

By building on the shared foundations of Mechanical Engineering and Data Science, this program provides a streamlined, cost-effective path to dual expertise. It enhances career prospects by equipping students with interdisciplinary skills relevant to modern engineering challenges.

 

Admission to the Program

New students should apply to the Mechanical Engineering graduate program for admission and indicate their interest in pursuing the dual Mechanical/Engineering Data Science MS degree. To be unconditionally admitted to the Dual M.S. program, an applicant should have:

  • A Bachelor's degree in Mechanical Engineering or in an engineering-related field, preferably from an accredited engineering program.
  • A grade point average of at least 3.00 out of 4.00 on the last 60 semester credit hours attempted exclusive of grades received for activities such as seminars, physical education, industrial internships, etc.
  • Optional: An adequate score on the Graduate Record Examination (GRE). Texas law prohibits the definition of minimum acceptable scores on the GRE. However, 160 to 163 is a typical average score on the Quantitative section across all degree programs for an admission class.
  • Three letters of recommendation attesting to the student’s capacity to perform in the classroom and (for applicants to the thesis program) in a research capacity. A minimum of two letters should be from tenured or tenure-track faculty members who have observed the academic performance of the applicant, and one can come from an engineering industry supervisor.
  • A statement of purpose that is consistent with the areas of instruction and (for applicants to the thesis program) the current research areas within the Department.

Acceptance to the program is based on a competitive combination of academic background, recommendation letters and the statement of purpose. Domestic applicants who are not clearly competitive in all three areas may be admitted on a conditional basis at the discretion of the Director of Admissions. Nonimmigrant visa holders may not be admitted conditionally.

Students may begin their graduate studies in one program and apply for admission to the dual degree program at a later date. However, the decision by a student to pursue the dual degree should be made prior to the completion of 18 hours of coursework.

 

Program of Study

Within the forty-five (45) required credit hours, students must complete the key course requirements for each degree (fifteen (15) hours for MME and fifteen (15) hours for MSEDS), while leveraging fifteen (15) hours of shared elective courses. This structure reduces the total number of credit hours from sixty (60), required to pursue both degrees separately, to forty-five (45). The shared elective courses must be carefully chosen from the approved course list; any courses outside this list require petition approval to ensure they effectively integrate data science with mechanical engineering.

  • Fifteen (15) hours of Mechanical Engineering courses from the MECE 6000-level or above, exclusive of graduate seminar (MECE 6111) and Graduate Project (MECE 6368)
  • Fifteen (15) hours of Data Science courses, which include:

    • Nine (9) hours of Data Science core courses from the following list.

      Course Code

      Course Name

      Credit Hours

      EDS 6333
      or
      INDE 6333

      Probability and Statistics
      or
      Probability and Statistics for Engineers

      3

      EDS 6340

      Introduction to Data Science

      3

      EDS 6342

      Introduction to Machine Learning

      3

    • Six (6) hours of Data Science prescribed elective courses from the following list.

      Course Code

      Course Name

      Credit Hours

      INDE 7397
      or
      PETR 6397

      Big Data and Analytics
      or
      Big Data Analytics

      3

      ECE 6364
      Or
      EDS 6397

      Digital Image Processing   
      Or
      Digital Image Processing for Data Science

      3

      ECE 6397

      Signal Processing and Networking for Big Data Applications

      3

      EDS 6344

      AI for Engineers

      3

      EDS 6346

      Data Mining for Engineers

      3

      EDS 6348

      Introduction to Cloud Computing

      3

      ECE 6342

      Digital Signal Processing

      3

      INDE 7397

      Engineering Analytics

      3

      INDE 6372

      Advanced Linear Optimization

      3

      EDS 6397

      Information Visualization

      3

      EDS 6397

      Natural Language Processing for Engineers

      3
  • Fifteen (15) hours of general elective courses shared by both Mechanical Engineering and Data Science, which include:

    • Six (6) hours of Data Science general elective courses from the following list.

      Course Code

      Course Name

      Credit Hours

      BIOE 6305

      Brain Machine Interfacing

      3

      BIOE 6306

      Advanced Artificial Neural Networks

      3

      BIOE 6309

      Neural Interfaces

      3

      BIOE 6340

      Quantitative Systems Biology & Disease

      3

      BIOE 6342

      Biomedical Signal Processing

      3

      BIOE 6346

      Advanced Medical Imaging

      3

      BIOE 6347

      Introduction to Optical Sensing and Biophotonics

      3

      BIOE 6345

      Biomedical Informatics

      3

      BZAN 6354
      Or 
      EDS 6397

      Database Management for Business Analytics
      Or 
      Database Management Tools

      3

      CIVE 6393

      Geostatistics

      3

      CIVE 6380

      Introduction to Geomatics/Geosensing

      3

      CIVE 6382

      Lidar Systems and Applications

      3

      CIS 6397

      Python for Data Analytics

      3

      CHEE 6367

      Advanced Proc Control

      3

      ECE 6376

      Digital Pattern Recognition

      3

      ECE 6397

      Sparse Representations in Signal Processing

      3

      ECE 6337

      Stochastic Processes in Signal Processing and Data Science 

      3

      ECE 6378

      Power System Analysis

      3

      ECE 6342

      Digital Signal Processing

      3

      ECE 6333

      Signal Detection and Estimation Theory

      3

      ECE 6315

      Neural Computation

      3

      ECE 6397

      GPU Programming

      3

      ECE 6397

      High Performance Computing

      3

      ECE 6325

      State-Space Control Systems

      3

      INDE 6370

      Operation Research-Digital Simulation

      3

      INDE 6336

      Reliability Engineering

      3

      INDE 7340

      Integer Programming

      3

      INDE 7342

      Nonlinear Optimization

      3

      INDE 6363

      Statistical Process Control

      3

      IEEM 6360

      Data Analytics for Engineering Managers

      3

      MECE 6379

      Computer Methods in Mechanical Design

      3

      MECE 6397

      Data Analysis Methods

      3

      MECE 6397

      Machine Learning

      3

      MECE 6397

      Learning Meets System and Control

      3
    • Nine (9) hours of elective courses from: (1) the MECE 6000-level or above courses, (2) the list of Engineering Data Science approved elective courses, or (3) a list of approved courses in the College of Engineering, the College of Natural Science and Mathematics, the Bauer College of Business, and the UH Law Center at 6000-level or above. Other courses not listed above may be considered but require petition approval.

In summary, fifteen (15) hours of Mechanical Engineering courses and fifteen (15) hours of shared general elective courses count toward the completion of the MME degree, while fifteen (15) hours of Engineering Data Science courses and fifteen (15) hours of shared general elective courses count toward the completion of the MSEDS degree.

 

Graduation Requirements

The graduation requirements for the dual-degree program are: a) At least a 3.00/4.00 grade point average over all courses, and b) A 3.00/4.00 grade point average over courses comprising the MECE courses and the approved Engineering Data Science courses.