What courses are available in the Online Master's?

The Online Master's at Purdue Mechanical Engineering gives you the ultimate flexibility. You have the freedom to choose any ME course you have an interest in, to further your career skills and knowledge.

ME Courses  |  Math Courses  |  Technical Electives  |  Not Allowable  |  FAQ

Base Requirements    

The Online MSME consists of 30 credit hours of graduate-level courses (50000-level and above) and includes 1-, 2-, and 3-credit hour courses. All courses must be technical and quantitative in content.

You will create a plan of study (POS) during the 3rd-6th week of your first semester that lists the courses you plan to take and when you plan to take them.  This is your initial plan and can be updated as things change, as long as changes keep you in degree compliance.


Mechanical Engineering Courses    

Here is a list of available Online MSME courses, sorted by potential interest area. Please note: you are not required to take specific groups or areas of classes; you are free to take any of the ME graduate-level classes that interest you.

Design

ME51100 Heat Transfer in Electronic Systems
ME51300 Engineering Acoustics
ME51800 Analysis of Thermal Systems
ME53900 Introduction to Scientific Machine Learning
ME54000 Internal Combustion Engine
ME54100 Engineering Design: A Decision-Based Perspective
ME55300 Product and Process Design
ME55400 Intellectual Property for Engineers
ME55600 Lubrication, Friction and Wear
ME55700 Design for Manufacturability
ME55900 Micromechanics of Materials
ME57000 Machine Design
ME57100 Reliability Based Design
ME57500 Theory and Design of Control Systems
ME57700 Human Motion Kinetics
ME58100 Numerical Methods in Mechanical Engineering
ME59700 Data Analytics for Scientists and Engineers
ME59700 Decision Making in Engineering Design
ME68100 Finite & Boundary Element Methods

Dynamics & Vibration

ME51300 Engineering Acoustics
ME53300 Turbomachinery
ME53900 Introduction to Scientific Machine Learning
ME54000 Internal Combustion Engine
ME55400 Intellectual Property for Engineers
ME55600 Lubrication, Friction and Wear
ME55900 Micromechanics of Materials
ME56200 Advanced Dynamics
ME56300 Mechanical Vibrations
ME57000 Machine Design
ME57100 Reliability Based Design
ME58100 Numerical Methods in Mechanical Engineering
ME59700 Complex Fluids
ME59700 Data Analytics for Scientists and Engineers
ME59700 Decision Making in Engineering Design
ME61100 Principles of Turbulence
ME61400 Computational Fluid Dynamics
ME68100 Finite & Boundary Element Methods

Fluid Mechanics

ME50900 Intermediate Fluid Mechanics
ME51000 Gas Dynamics
ME51300 Engineering Acoustics
ME52500 Combustion
ME53300 Turbomachinery
ME53900 Introduction to Scientific Machine Learning
ME54000 Internal Combustion Engine
ME55400 Intellectual Property for Engineers
ME55900 Micromechanics of Materials
ME57000 Machine Design
ME57100 Reliability Based Design
ME58100 Numerical Methods in Mechanical Engineering
ME59700 Complex Fluids
ME59700 Data Analytics for Scientists and Engineers
ME59700 Decision Making in Engineering Design
ME61100 Principles of Turbulence
ME61400 Computational Fluid Dynamics
ME68100 Finite & Boundary Element Methods

Heat & Mass Transfer

ME50000 Advanced Thermodynamics
ME50100 Statistical Thermodynamics
ME50500 Intermediate Heat Transfer
ME51100 Heat Transfer in Electronic Systems
ME51800 Analysis of Thermal Systems
ME53300 Turbomachinery
ME53900 Introduction to Scientific Machine Learning
ME54000 Internal Combustion Engine
ME55400 Intellectual Property for Engineers
ME57000 Machine Design
ME57100 Reliability Based Design
ME58100 Numerical Methods in Mechanical Engineering
ME59700 Complex Fluids
ME59700 Data Analytics for Scientists and Engineers
ME59700 Decision Making in Engineering Design
ME60800 Numerical Methods in Heat, Mass, and Momentum Transfer
ME61100 Principles of Turbulence
ME61400 Computational Fluid Dynamics
ME68100 Finite & Boundary Element Methods

Solid Mechanics

ME51300 Engineering Acoustics
ME53300 Turbomachinery
ME53900 Introduction to Scientific Machine Learning
ME55400 Intellectual Property for Engineers
ME55600 Lubrication, Friction and Wear
ME55700 Design for Manufacturability
ME55900 Micromechanics of Materials
ME57000 Machine Design
ME57100 Reliability Based Design
ME57700 Human Motion Kinetics
ME58100 Numerical Methods in Mechanical Engineering
ME59700 Data Analytics for Scientists and Engineers
ME59700 Decision Making in Engineering Design
ME61100 Principles of Turbulence
ME65000 Computational Fracture Mechanics
ME68100 Finite & Boundary Element Methods

Systems, Measurements, & Controls

ME51100 Heat Transfer in Electronic Systems
ME53300 Turbomachinery
ME53900 Introduction to Scientific Machine Learning
ME54000 Internal Combustion Engine
ME55400 Intellectual Property for Engineers
ME55900 Micromechanics of Materials
ME57000 Machine Design
ME57100 Reliability Based Design
ME57500 Theory and Design of Control Systems
ME57800 Digital Control
ME57900 Fourier Methods in Digital Signal Processing
ME58100 Numerical Methods in Mechanical Engineering
ME59700 Data Analytics for Scientists and Engineers
ME59700 Decision Making in Engineering Design
ME68100 Finite & Boundary Element Methods

Thermodynamics

ME50000 Advanced Thermodynamics
ME50100 Statistical Thermodynamics
ME50500 Intermediate Heat Transfer
ME51100 Heat Transfer in Electronic Systems
ME51800 Analysis of Thermal Systems
ME52500 Combustion
ME53300 Turbomachinery
ME53900 Introduction to Scientific Machine Learning
ME54000 Internal Combustion Engine
ME55400 Intellectual Property for Engineers
ME57700 Human Motion Kinetics
ME58100 Numerical Methods in Mechanical Engineering
ME59700 Complex Fluids
ME59700 Data Analytics for Scientists and Engineers
ME59700 Decision Making in Engineering Design
ME60800 Numerical Methods in Heat, Mass, and Momentum Transfer
ME61400 Computational Fluid Dynamics
ME68100 Finite & Boundary Element Methods


Approved Applied Math Courses for Online MSME

The below courses can be used to meet 3 credits of the online master’s math requirements; the other 3 credits must be directly from the Math department (MA 511, MA 527, or MA 528).  

Approved Applied Math Courses in ME

ME 53900 Introduction to Scientific Machine Learning
ME 58000 Nonlinear Engineering Systems
ME 58100 Numerical Methods in Mechanical Engineering
ME 60800 Numerical Methods in Heat, Mass and Momentum Transfer
ME 61200 Continuum Mechanics
ME 61400 Computational Fluid Dynamics
ME 68100 Finite & Boundary Element Methods

Approved Applied Math Courses from Other Schools

CE 59500 Finite Elements in Elasticity
CS 51500 Matrix Computations
CS 57700 Natural Language Processing
CS 57800 Statistical Machine Learning
ECE 58000 Optimization Methods for Systems and Control
ECE 60000 Random Variables and Signals
ECE 60200 Lumped System Theory
IE 54500 Engineering Economic Analysis
IE 54600 Economic Decisions in Engineering
IE 69000 Stochastic Network Analysis
STAT 51100 Statistical Methods
STAT 51200 Applied Regression Analysis
STAT 51400 Design of Experiments
STAT 51600 Basic Probability & Applications
STAT 52200 Sampling & Survey Techniques
AAE 51200 Computational Aerodynamics
AAE 51600 Computational Fluid Mechanics
AAE 55300 Elasticity in Aerospace Engineering
AAE 55800 Finite Element Methods in Aerospace Structures
AAE 60300 Theoretical Methods in Engineering Science I
AAE 60400 Theoretical Methods in Engineering Science II
PHYS 570Q Stochastic Processes in Physics
PHYS 60000 Methods of Theoretical Physics I
PHYS 60100 Methods of Theoretical Physics II

These courses are NOT allowed on the Plan of Study to satisfy the Math requirement:    

ME 56200 Kinematics
ME 57900 Fourier Methods in Digital Signal Processing
MA 58000 History of Mathematics
MSE 69700 Atomistic view of materials: Modeling & Simulations
STAT 50100 Experimental Statistics I
STAT 51300 Statistical Quality Control

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Non-ME Technical Electives    

Please find below, allowable technical elective courses for the ME Online Degree Program and can be added to your Plan of Study. This list is not all-inclusive, so if you're interested in taking a course that you do not see below, and is not on the personal enrichment/non-allowable course list, please email sltague@purdue.edu, the course abbreviation/number/title for status. (All ME lecture-based courses are allowable to meet degree requirements and will not show up on this list.)

AAE 507 Principles of Dynamics
AAE 511 Intro to Fluid Mechanics
AAE 512 Computational Aerodynamics
AAE 514 Intermediate Aerodynamics
AAE 516 Computational Fluid Mechanics
AAE 520 Experimental Aerodynamics
AAE 523 Intro to Remote Sensing
AAE 532 Orbit Mechanics
AAE 537 Hypersonic Propulsion
AAE 538 Air Breathing Propulsion
AAE 545 Dynamic Behavior of Materials
AAE 548 Mechanical Behavior of Aerospace Materials
AAE 550 Multidisciplinary Design Optimization
AAE 552 Nondestructive Eval of Structures
AAE 553 Elasticity in Aerospace Eng
AAE 554 Fatigue Struct & Materials
AAE 555 Mechanics of Composite Materials
AAE 558 Finite Element Methods in Aerospace Structures
AAE 560 Systems of Systems Modeling & Analysis
AAE 561 Intro to Convex Optimization
AAE 564 Systems Analysis & Synthesis
AAE 590 Molecular Gas Dynamics
AAE 590 Multi-Agent Autonomy & Control
AAE 590 Aerospace Propulsion
AAE 590 Mfg of Adv Composites
AAE 590 Plasma Laboratory
AAE 603 Theoretical Methods in Eng Sci I
AAE 604 Theoretical Methods in Eng Sci II
AAE 626 Turbulence & Turbulence Modeling
AAE 648 Modeling Damage & Strengthening Mechanics in Materials
AAE 654 Fracture Mechanics
AAE 666 Non Linear Dynamics, Systems & Controls
AAE 668 Hybrid System Theory & Applications
AAE 690 Liquid Propellant Chemistry & Applications
ABE 627 Colloidal Phenomena in Bioprocessing
AGRY 535 Boundary Layer Meteorology
BME 511 Biomedical Signal Processing
BME 581 Fundamentals of MEMS and Micro-Integrate
BME 595/ABE 591 Polymeric Biomaterials
BME 595 Bio-Micro-Electro-Mechanical Systems & Miomed Microsys
BME 695 Deep Learning
BME 695/ECE 641 Model-Based Image & Signal Processing
BMS 598 Basic Bone Biology
CE 513 Lighting in Buildings
CE 51501 Building Energy Audits
CE 570 Adv Structural Mechanics
CE 595 Finite Elements in Elasticity
CE 597 Subsurface Hydrology
CE 597 Nonlinear Fracture Mechanics
CE 597/CE 52201 Fundamentals of Building Info Modeling
CE 597/CE 52202 BIM in Construction
CE 595 Theory of Elasticity Review
CE 697 Photochemical Reactors: Theory, Methods, Applications of Ultraviolet Radiation
CHE 544 Structure & Physical Behavior of Polymer Systems
CHE 554 Smart Mfg in Process Industries
CHE 597 Finite Element Analysis in Chemical Engineering
CHE 597 Organic Electronic Materials & Devices
CHE 632 Linear Operators in Engineering
CHE 668 Colloidal & Interfacial Phenomena
CHE 697 St Instability & Trans Phen
CHM 538 Molecular Biotechnology
CHM 696 Bio-Nanotechnology
CS 501 Computing for Sci & Eng
CS 514 Numerical Methods
CS 515 Numerical Linear Algebra
CS 536 Data Communication & Computer Networks
CS 573 Data Mining
CS 577 Natural Language Processing (3cr)
CS 578 Statistical Machine Learning
CS 590 Machine Learning Method for NLLP
CS 590 Generative Methods in Computer Graphics
CSCI 557 Image Processing/Computer Vision
ECE 50631/ECE 595 Fundamentals of Current Flow
ECE 50632/ECE 595 Intro to Quantum Transport
ECE 50633/ECE 595 Boltzmann Law:  Physics to Computing
ECE 51012 Electromechanics
ECE 51018 Hybrid Electric Vehicles
ECE 538 Digital Signal Processing I
ECE 544 Digital Communications
ECE 552 Intro to Lasers
ECE 563 Programming Parallel Machines
ECE 568 Embedded Systems
ECE 570 Artificial Intelligence
ECE 580 Optimization Methods for Systems & Control
ECE 595 Intro to Data Mining
ECE 595/ECE 50632 Intro to Quantum Transport
ECE 595 Semiconductor Fundamentals
ECE 595 Fundamentals of Current Flow
ECE 595 Intro to Deep Learning
ECE 595/STAT 598 Machine Learning I
ECE 595 Machine Learning II/Intro to Deep Learning
ECE 595 Intro to Quantum Sci & Tech
ECE 595 Deep Learning for Computer Vision
ECE 595/ECE50633 Boltzmann Law: Physics to Computing
ECE 600 Random Variables and Signals
ECE 602 Lumped System Theory
ECE 60421 Nanophotonics & Metamaterials
ECE 60423/ECE 695 RF System Design
ECE 608 Computational Models and Methods
ECE 610 Energy Conversion
ECE 629 Intro Neural Networks
ECE 637 Digital Image Processing I
ECE 641/BME 695 Model-Based Image & Signal Processing
ECE 647 Performance Modeling of Comp Comm Networks
ECE 661 Computer Vision
ECE 675 Intro to Analysis of Non-Linear Systems
ECE 680 Modern Automatic Control
ECE 695 Large Scale Networks
ECE 695/60423 RF System Design
ECE 695 Intro to Math for Systems & Control Theory
ECE 695/ECE 61010 Time Domain Simulation & Optimization
ECE 695 Quantum Detectors & Sensors
ECE 695/BME 646 Deep Learning Theory & Practice of Deep Neural Networks
EEE 530 Life Cycle Assessment: Principles and Applications
EEE 595 Indoor Air Quality
IE 530 Quality Control
IE 533 Industrial Application of Statistics
IE 537 Discrete Optimization Models & Algorithms
IE 538 Nonlinear Optimization
IE 541 Nature-Inspired Computing
IE 545 Engineering Economic Analysis
IE 546 Economic Decisions in Engineering
IE 561 Intro to Convex Optimization
IE 566 Production Control Management
IE 570 Adv Mfg Processes
IE 574 Industrial Robotics & Flexible Assembly
IE 577 Human Factors in Engineering
IE 579 Design & Control of Prod & Mfg Systems
IE 588 eWork and e-Service
IE 590/IE 578 Applied Ergonomics
IE 590 Electrotechnical Robotic Systems
IE 590 Deep Learning in Machine Vision
IE 659 Human Aspects in Computing
IE 690 Stochastic Network Analysis
MA 598 Math Theory Apps Deep Learning (Fall 20)
MA 598 Math Neural Networks (Sp19)
MSE 508 Phase Transformation in Solids
MSE 510 Microstructural Characterization Techniques
MSE 523 Physical Ceramics
MSE 527 Intro to Biomaterials
MSE 530 Materials Processing in Mfg
MSE 531 Quantitative Analysis of Microstructure
MSE 550 Properties of Solids
MSE 597 Kinetics of Materials
MSE 597 Additive Mfg of Materials
MSE 597 Into to Materials Sci of Rechargeable Batteries
MSE 597 Mechanical Behavior of Polymers
MSE 597 Modeling & Simulation of Materials
MSE 600 Materials Eng Fundamentals
MUCL 501 Nuclear Engineering Principles
NUCL 570 Fuzzy Approaches in Eng
NUCL 575 Neural Computing Engr
PHYS 545 Solid State Physics
PHYS 570Q Stochastic Processes in Physics
PHYS 600 Methods of Theoretical Physics I
PHYS 601 Methods of Theoretical Physics II
PHYS 660 Quantum Mechanics I
STAT 511 Statistical Methods
STAT 512 Applied Regression Analysis
STAT 513 Statistical Quality Control
STAT 514 Design of Experiments
STAT 516 Basic Probability & Applications
STAT 522 Sampling & Survey Techniques
SYS 50000 Perspectives on Systems
SYS 51000 Tools and Methodologies for Designing Systems
SYS 53000 Practical Systems Thinking

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Not Allowable    

Please find below, courses that can be taken as personal enrichment, but are not allowable to meet degree requirements for the ME Online Degree Program. This list is not all-inclusive, so if you don't see a course listed on the allowable technical elective course list, or below, please email sltague@purdue.edu, the course abbreviation/number/title for status.

AAE 590 Space Flight Operations
AAE 590 System Safety & Reliability
BME 521 Biosensors:   Fundamentals and Applications
BME 553 Biomedical Optics
BME 561 BME 56100 - Preclinical and Clinical Study Design
BME 562 Regulatory Issues Surrounding Approval of Biomedical Devices
BME 563 Quality Systems for Regulatory Compliance
BME 564 Ethical Engineering of Medical Devices
BME 595 Medical Imaging Diagnostic Tech
BME 683 Polymers Pharma & Biol Sys
CE 597 Global Sustainable Engineering
CE 597 UAS Based Mapping Basic Principles
CE 597 UAS Based Photogrammetric Mapping
CE 597 UAS Based LiDAR Mapping
CE 597 Plastics in Infrastructure and the Environment
CE 597 Disasters and Emergencies
CE 597 Smart Logistics & Supply Chains
CEM 597 Requirements & Implementation of ISO 41001
CEM 597 High Tech Entrepreneurship
CHE 597 Analytical Approach to Healthcare Delivery
ECE 595 An Introduction to Data Analysis, Design of Experiment & Machine Learning
ECE 595 Communication for Engineering Leaders
ECE 595 Natural Language Processing
ENE No courses from engineering education are allowable to meet degree requirements
GRAD No courses starting with 'GRAD' are allowable to meet ME degree requirements
IE 558 Safety Engineering
IE 566 Job Design
IE 590 Project Management
IE 590 Human Factors & Medical Devices
IE 590/IE 595 Risk Analytics for Eng Mgmt & Public Policy
MSE 597 Lean Manufacturing
PHYS 560 Stellar Evolution
STAT 540 Mathematics of Finance
STAT 597 Data Mine I or II
SYS 590 Systems Engineering Processes & Professional Competencies
TECHNOLOGY  No courses from technology are allowable to meet ME degree requirements
TDM 511 Data Mine

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Online MSME Curriculum: Frequently Asked Questions    

Is there a minimum course registration required each semester?

  • You need to register for at least one credit to be considered an active student. If you do not enroll for more than two consecutive semesters, you will lose your student status and would have to reapply.
  • While you can take extra courses each semester, at least one course every semester should be taken that can count toward degree requirements.
  • Students pursuing the degree part-time, should enroll in no more than 1-2 courses a semester at most.

Are all courses available every term?

Are courses required during the summer?

  • No. It’s your decision. There are very limited grad level engineering courses offered in summer. You can take math/statistics if you like.  Please keep in mind, summer courses are very condensed, so it’s not recommended to take more than one course.

Can I take additional courses that don’t apply toward degree requirements?

  • As long as you register in grad-level courses (500- or 600-level), you can take courses that don’t apply to your degree requirements before the end of your last semester.  But you should always take at least one course a semester that does apply toward your degree requirements.

How are the online courses structured?

  • Online engineering graduate students take courses asynchronously, meaning course content can be accessed from anywhere at any time. Students view the lectures and course materials weekly on their own schedule in order to complete the assignments and tests. There are due dates for assignments and exams, and these dates are listed on the course syllabi. Lectures are available for download and viewing two hours after the "live" lecture has been recorded.

Can courses taken at another University be transferred?

  • Transfer courses may be accepted if they have not been used to meet another degree requirement, are grad-level (500- or 600-level), technical and quantitative in content, received a B or better grade, and were recently taken. Once you’re a registered student, you’ll submit your transfer course description/syllabus to the ME Grad Office for review. If it’s approved by ME, you’ll add it to your plan of study. Then the Grad School will review and make final decision on what they’ll accept. You can transfer no more than 12 credit hours.  We cannot tell you in advance of admission as to what courses will be allowed to transfer.  Transfer credits will count toward your tech elective requirement of the degree.

Do I need to maintain a minimum GPA?

  • You must complete all courses on your plan of study (POS) with a grade of no less than a C (no less than a "C-" if admitted before Summer 2022). No grades of C-, D, or F are allowed on your POS; any plan of study course with a grade of D or F must be repeated. You cannot drop them from your POS. You must have a POS GPA of 3.0 to complete the MSME degree in good standing with the Graduate School. Students with a GPA lower than 3.0 after 12 credit hours will receive a warning letter the first semester; if the GPA doesn’t improve, you may be dismissed from the program. Graduate-level transfer courses are not included in your GPA calculation. 

Is there a time limit to complete the degree?

  • Most students will complete the online MSME in 1-3 years. However, you have up to 4 years to complete your degree. If you do not enroll after two consecutive semesters (approximately 1 calendar year), you will become inactive and must reapply to Purdue. To be in active status, at least one credit hour of registration is required.

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