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Nuclear Engineering Concentration Requirements

The Interdisciplinary Engineering (MSE or MS) degree requires a total of 30 credit hours with at least 18 hours of Purdue, graduate level, engineering courses as a base requirement. The Nuclear Engineering (NE) concentration requirements must be met within these base requirements. 

Degree requirements checklist:

_____ total core NE courses (9 hours)
_____ total other engineering courses (9 hours)
_____ total other elective courses (12 hours)
_____ total credit hours (30 hours)

Note: At least 18 hours must be graduate level, engineering courses taken at Purdue University.

Required (9 hours):  Core NE Courses

Required (9 hours): Other Engineering* Courses

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Elective Courses (12 hours): Other engineering* and/or non-engineering** courses

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Total: 30 hours

More Online Nuclear Engineering Courses

  • NUCL50200 Nuclear Engineering Systems - A second course for graduate students desiring a nuclear engineering sequence and an elective for students in science or engineering. Course topics include principles and practice of nuclear power plant systems with design applications, reactor kinetics, reactor control, radiation protection, shielding, nuclear fuels, fuel cycles, waste management, thermal cycles, heat transport, thermal hydraulics, reactor accidents, and safety analysis.
  • NUCL57000 Fuzzy Approaches in Engineering - Course topics include Intellectual Framework, basics, Fuzzy Models and Formal Structures, Fuzzy Control, General Principles of Rule-Based Systems Development and Limitations, and Advanced Topics.
  • NUCL57500 - Neural Computer in Engineering - The course presents the mathematical fundamentals of computing with neural networks and a survey of engineering applications. Computational metaphors from biological neurons serve as the basis for artificial neural networks modeling complex, non-linear and ill-posed problems. Applications emphasize the engineering utilization of neural computing to diagnostics, control, safety, and decision-making problems. Course topics include: Basics, Backpropagation, and Related Training Algorithms, Feedback and Other Special Neural Networks, Dynamic Neural Networks and Control Systems, Practical Aspects of Using Neural Networks, and Advanced Topics
  • NUCL 59700 Big Data and Machine Learning in Engineering - This course familiarizes students with key information technologies and their underlying methods and techniques that are used to store, manipulate, analyze and exploit large volumes of data with an emphasis in engineering applications and particularly nuclear data.

* Engineering courses  are offered by engineering schools and/or taught by engineering faculty such as AAE-Aeronautics & Astronautics, ABE - Agricultural & Biological Engineering, BME-Biomedical Engineering, CE-Civil Engineering, ECE-Electrical & Computer Engineering, EEE - Environmental & Ecological Engineering, IE-Industrial Engineering, ME-Mechanical Engineering, MSE - Materials Engineering, NUCL -Nuclear Engineering, SYS - Systems Engineering. 

 **Examples of non-engineering courses are BIOL - Biological Sciences, CS-Computer Science, GRAD-Graduate studies, MA-Mathematics, STAT-Statistics, etc. Only the specific non-engineering courses listed within the courses by school list are acceptable on an engineering plan of study.

The student is ultimately responsible for knowing and completing all degree requirements. This website is a knowledge source for specific requirements and completion.

Note: This checklist is an aid to help you understand the program requirements and map out a plan. The actual electronic plan of study ePOS is submitted via myPurdue during the first semester you're registered after admission to a degree program.