Rationale for the Program
Graduate students with a keen interest in both Aerospace Engineering and Engineering Data Science have the opportunity to pursue a dual degree program that strategically integrates courses from both disciplines. This innovative Dual Aerospace Engineering/Data Science Master's degree program enables students to earn both a Master of Science in Aerospace Engineering (MSAE) 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 Aerospace 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 aerospace 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 Aerospace 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 Aerospace Engineering/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, Aerospace 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.
- 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 rec¬ommendation 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 core and major course requirements for each degree (fifteen (15) hours for MSAE 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 aerospace 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 Aerospace Engineering core courses from the following core areas.
- Aerodynamics and Heat Transfer
- Structural Mechanics and Materials
- Controls and Dynamics
Students can select a core area of concentration where they take the majority of their core courses. However, as a breadth requirement, students should take at least six semester hours of core course work outside their core area of concentration. The remaining twelve semester hours of graduate work should be completed with courses from the above core areas or from approved graduate elective courses.
- 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 6333Probability and Statistics
or
Probability and Statistics for Engineers3
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 6397Big Data and Analytics
or
Big Data Analytics3
ECE 6364
Or
EDS 6397Digital Image Processing
Or
Digital Image Processing for Data Science3
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 Aerospace Engineering and Data Science, which include:
-
Nine (9) hours of approved Aerospace Engineering elective courses from the following list.
Course Code
Course Name
Credit Hours
MECE 6363
Physical Metallurgy
3
SPAC 6201
Man Systems Integration
3
SPAC 6401
Space Systems Technology Studio
3
SPAC 6203
Spacecraft and Habitat Design
3
SPAC 6403
Mission Planning and Analysis
3
SPAC 6404
Mission Planning and Analysis II
3
SPAC 6405
Advanced Design and Analysis
3
ECE 6315
Neural Computation
3
ECE 6331
Advanced Telecommunications
3
ECE 6333
Signal Detection and Estimation Theory
3
ECE 6336
Advanced Microprocessor Systems
3
ECE 6337
Stochastic Processes Signal Processing
3
EECE 6367
Computer Architecture and Design
3
INDE 6332
Engineering Project Management
3
INDE 6336
Reliability Engineering
3
INDE 6337
Human Factors Systems Engineering
3
INDE 6365
Engineering Economy
3
INDE 6386
Innovation management and Entrepreneurship
3
INDE 7383
Systems Engineering
3
PHYS 7324
Plasma Physics
3
- Other graduate courses can be applied to the program as elective courses, subject to the approval of the Program Director.
-
-
Six (6) hours of approved Engineering Data Science 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
Database Management for Business Analytics
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 Aerospace Engineering courses and fifteen (15) hours of shared general elective courses count toward the completion of the MSAE 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 on the courses comprised of the approved aerospace Engineering core area 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 Aerospace Engineering core courses from the following core areas.
- Aerodynamics and Heat Transfer
- Structural Mechanics and Materials
- Controls and Dynamics
Students can select a core area of concentration where they take the majority of their core courses. However, as a breadth requirement, students should take at least six semester hours of core course work outside their core area of concentration. The remaining twelve semester hours of graduate work should be completed with courses from the above core areas or from approved graduate elective courses.
- 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 6333Probability and Statistics
or
Probability and Statistics for Engineers3
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 6397Big Data and Analytics
or
Big Data Analytics3
ECE 6364
Or
EDS 6397Digital Image Processing
Or
Digital Image Processing for Data Science3
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 Aerospace Engineering and Data Science, which include:
-
Three (3) hours of approved Aerospace Engineering elective courses from the following list.
Course Code
Course Name
Credit Hours
MECE 6363
Physical Metallurgy
3
SPAC 6201
Man Systems Integration
3
SPAC 6401
Space Systems Technology Studio
3
SPAC 6203
Spacecraft and Habitat Design
3
SPAC 6403
Mission Planning and Analysis
3
SPAC 6404
Mission Planning and Analysis II
3
SPAC 6405
Advanced Design and Analysis
3
ECE 6315
Neural Computation
3
ECE 6331
Advanced Telecommunications
3
ECE 6333
Signal Detection and Estimation Theory
3
ECE 6336
Advanced Microprocessor Systems
3
ECE 6337
Stochastic Processes Signal Processing
3
EECE 6367
Computer Architecture and Design
3
INDE 6332
Engineering Project Management
3
INDE 6336
Reliability Engineering
3
INDE 6337
Human Factors Systems Engineering
3
INDE 6365
Engineering Economy
3
INDE 6386
Innovation management and Entrepreneurship
3
INDE 7383
Systems Engineering
3
PHYS 7324
Plasma Physics
3
- Other graduate courses can be applied to the program as elective courses, subject to the approval of the Program Director.
-
-
Three (3) hours of approved Engineering Data Science 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
Database Management for Business Analytics
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 Aerospace Engineering core courses, nine (9) hours of thesis, and six (6) hours of shared general elective courses count toward the completion of the MSAE 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.
Graduation Requirements
The graduation requirements for the dual-degree program are: At least a 3.00/4.00 grade point average over all courses, and b) A 3.00/4.00 grade point average on the courses comprised of the approved aerospace Engineering core area courses and the approved Engineering Data Science courses.