Dual M.S. Degree in Mechanical Engineering 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 coursework from both disciplines. This innovative Dual Mechanical Engineering/Data Science Master's degree program enables students to earn both a Master of Science in Mechanical Engineering (MSME) 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, which enables 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 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.
A minimum score of 6.5 on the IELTS or 79 on the internet-based TOEFL examination for students whose native language is not English.
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 eighteen (18) hours of coursework.

Program of Study

Within the forty-five (45) required credit hours, students must complete the core and major course requirements for each degree (fifteen (15) hours for MSME 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. Students may also choose to complete the program with a Thesis option in which case they will earn an M.S. with Thesis degree.

Specific plan of study requirements for the Dual M.S. Program without Thesis and the Dual M.S. Program with Thesis are outlined below:

Program of Study for the Dual M.S. Program without Thesis

Fifteen (15) hours of Mechanical Engineering courses, which include:

Three (3) hours from the course MECE 6384 Methods of Applied Mathematics I.

Nine (9) hours of Mechanical Engineering core courses from the following list.

Course Code	Course Name	Credit Hours
MECE 6384	Methods of Applied Mathematics I	3
MECE 6367	Control Systems Analysis	3
MECE 6388	Optimal Control Theory	3
MECE 6361	Mechanical Behavior of Materials	3
MECE 6363	Physical Metallurgy	3
MECE 6364	Phase Transform in Materials	3
MECE 6377	Continuum Mechanics I	3
MECE 7397	Continuum Mechanics II	3
MECE 6334	Convection Heat Transfer	3
MECE 6345	Fluid Dynamics I	3

Three (3) hours of Mechanical Engineering elective course 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 7363	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 MSME 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.

Program of Study for the Dual M.S. Program with Thesis

Nine (9) hours of thesis

Fifteen (15) hours of Mechanical Engineering courses, which include:

Three (3) hours from the course MECE 6384 Methods of Applied Mathematics I.

Nine (9) hours of Mechanical Engineering core courses from the following list.

Course Code	Course Name	Credit Hours
MECE 6384	Methods of Applied Mathematics I	3
MECE 6367	Control Systems Analysis	3
MECE 6388	Optimal Control Theory	3
MECE 6361	Mechanical Behavior of Materials	3
MECE 6363	Physical Metallurgy	3
MECE 6364	Phase Transform in Materials	3
MECE 6377	Continuum Mechanics I	3
MECE 7397	Advanced Mechanics of Solids	3
MECE 6334	Convection Heat Transfer	3
MECE 6345	Fluid Dynamics I	3

Three (3) hours of Mechanical Engineering elective course 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 prescribed Data Science 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

Six (6) hours of general elective courses shared by both Mechanical Engineering and Data Science, which include:

Six (6) hours of general elective courses from the following list of Engineering Data Science approved elective courses, (2) the MECE 6000-level or above 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.

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

In summary, fifteen (15) hours of Mechanical Engineering courses, nine (9) hours of thesis, and six (9) hours of shared general elective courses count toward the completion of the MSME degree, while fifteen (15) hours of Engineering Data Science courses, nine (9) hours of thesis, and six (6) hours of shared general elective courses count toward the completion of the MSEDS degree.