Sample Courses in the Quantitative/Analytical Competency Area
Courses provide additional graduate level training in Advanced Math, Numerical Methods, Quantitative Analyses, and/or Data Science – should ideally include at least one course in statistics.
Purdue West Lafayette Courses
These courses CAN NOT be used on the plan of study:
- Seminar Courses
- Methodology/laboratory courses
- ENE (Engineering Education) Courses
- CS 515-- Numerical Linear Algebra
- PSY 600--Statistical Inference
- PSY 601--Correlation and Experimental Data
- SLHS 502--Fundamentals of Speech Production and Perception
- SOC 573--Human Side of Medicine (for thesis students; pmp students are allowed to take it)
- STAT 503--Stat Methods Biology
- STAT 511--Stat Methods
- STAT 512--Applied Regression Analysis
- STAT 516--Basic Probability and Application (for thesis students; pmp students are allowed to take it)
| Example of Acceptable Courses | Course Name |
|---|---|
| AAE 55400 | Fatigue Struct & Matls |
| BME 53200 | Bioelectronics |
| BME 50100 | Biostatistics |
| BME 51100 | Biomedical Signal Processing |
| BME 59500 | Applied Medical Imaging Processing and Analysis |
| BME 59500 | Continuum Models Biomed Engr |
| BME 59500 | Deep Learning |
| BME 63200 | Bioelectronics |
| BME 65500 | Multiscale Modeling |
| BME 69500 | Foundations Of Comp Imaging |
| BME 69500 | Model Based Image Processing |
| BME 69500 | Numerical Methods In BME |
| BME 69500 | Quantitative Systems Biology |
| CS 51400 | Numerical Analysis |
| CS 57800 | Statistical Machine Learning |
| CS 59000 | Computing for Life Sciences |
| ECE 57000 | Artificial Intelligence |
| ECE 60000 | Random Variables |
| ECE 60141 | Foundations Of Comp Imaging |
| ECE 60200 | Lumped System Theory |
| ECE 60400 | Electromagnetic Field Theory |
| ECE 63700 | Digital Image Processing |
| ECE 64100 | Model Based Image Processing |
| ECE 64500 | Estimation Theory |
| IE 53300 | Ind Application Stat |
| MA 51000 | Vector Calculus |
| MA 51100 | Linear Algebra Appl |
| MA 51400 | Numerical Analysis |
| MA 51900 | Intro to Probability |
| MA 52500 | Intro Complex Anly |
| MA 52700 | Adv Math Engr Phys I |
| MA 52800 | Adv Math Engr Phys II |
| ME 50300 | Micro and Nano Scale Energy Transfer Processes |
| ME 53900 (for PMP students) | Introduction to Scientific Machine Learning |
| ME 58000 | Nonlinear Engr Systems |
| ME 58700 | Engineering Optics |
| ME 61200 | Continuum Mechanics |
| MSE 59700 | Mechanical Properties and Behaviors of Polymers |
| PHYS 60000 | Methods Theoretical Physics I |
| PHYS 60100 | Methods Theoretical Physics II |
| STAT 51400 | Design Of Experiment |
| STAT 51700 | Statistical Inference |
| STAT 51900 | Intro To Probability |
| STAT 52400 | Appl Multiv Analysis |
| STAT 52800 | Intro Math Stat |
| STAT 52900 | Bayesian Appl Dec Thy |
| STAT 53200 | Elem Stochastic Proc |
| STAT 55300 | Linear Models |
Purdue Indianapolis Courses
| Example of Acceptable Courses | Course Name |
|---|---|
| BME 59500 | Experimental Methods in BME |
| BME 59500 | Neural Engineering |
| ECE 53800 | Digital Signal Processing |
| ECE 57000 | Artificial Intelligence |
| ECE 60000 | Random Variable and Signals |
| ECE 62900 | Introduction to Neural Networks |
| ME 59700 | Finite Element Analysis |