Course  Selection

Undergraduate

Each year, I talk with a number of undergraduate students who ask me for course suggestions and career advice.  I summarize my suggestions here and hope that will provide some guidance when you are making decisions.  I wish you all be very successful in coursework and enjoy the life in the Wolfpack family!

• 1. Core: Calculus I and II, Physics, Computer Systems, ECE Lab, Electric and Electronic Circuits, Linear Systems, Electromagnetic Fields, Programming, Matlab, Logic Design, Control, Analog and Digital Systems, Communication (good for SCADA and relay),

     • (Introduction: ECE109, ECE200, ECE209, ECE220, ECE211, ECE212)

     • (Foundation: ECE301, ECE302, ECE303, ECE305, ECE306, ECE308, ECE310)

• • Power System Related: 

    • ECE305 ECE 305 Principles of Electromechanical Energy Conversion

    • ECE 451 Power System Analysis

    • ECE 452 Renewable Electric Energy Systems

1. If you want to go take some graduate school courses in power system areas, here are the options

   • ECE550: Power System Operation and Control (Dr. Mesut Baran)

   • ECE551: Smart Electric Power Distribution Systems (Dr. David Lubkeman)

   • ECE552: Renewable Electric Energy Systems (Dr. Mesut Baran)

   • ECE516: Systems Control Engineering (Dr. Mo-Yuen Chow)

     • ECE534: Power Electronics 

       • Coursera: Power Electronics by Dr. Robert Erickson: Online Power Electronics

       • Fundamentals of Power Electronics - Course Introduction (KatKimshow): https://www.youtube.com/watch?v=aE4UPFvafaM&list=PLmK1EnKxphikP6c9Yc9kGYO0kvrbEoWN8

   • ECE585: Utility Business (Dr. Wenyuan Tang)

   • ECE586: Communication SCADA Smart Grid (Dr. David Lubkeman) 

   • ECE581: Electric Power System Protection (Dr. Mesut Baran)

   • ECE592: Topic#40: Power System Transients Analysis (Dr. David Lubkeman) 

   • ECE 592-074 Data Analytics for Power Engineering (Arnie de Castro (adecast@ncsu.edu), Wenyuan Tang (wtang8@ncsu.edu).

   • ECE753: Computational Methods for Power Grid Operation and Planning  (Dr. Ning Lu)

   • ECE726: Advanced Feedback Control (Dr. Aranya Chakrabortty)

   • ECE736: Power System Stability (Dr. Aranya Chakrabortty)

2. Electives: Find your specialization: Power Systems Basics, Protection Relay, Machine, Renewable Energy, Smart Distribution, Control, Signal Processing

   • Specialization in power: ECE305 (Principles of Electromechanical Energy Conversion), ECE451 (Power System Analysis), ECE452 (Renewable Electric Energy Systems), ECE434 (Fundamentals of Power Electronics), ECE 453 (Electric Motor Drives)

     • Signal Processing: ECE 435 (Elements of Control), ECE421 (Introduction to Signal Processing),

   • ECE407 (Introduction to Computer Networking) is useful if you are interested in communication related job (SCADA, relay, etc)

• 1. Prepare for the Fundamentals of Engineering (FE) exam: E490 FE Preparation course (looks like the pass rate of our ECE students is 22/23 between Jan-June 2017.

3. Senior Design: find a project in a power related area (Solar, Power Electronics, Battery, Electric Vehicles, Protection, etc.)

4. Co-op: Try to find a co-op position that allows you to rotate among a few positions.  This will give you a more complete view of an organization.  Co-op often leads to a better understanding of your course work and will make your resume stronger. 

5. Internship: Try to find an internship in power related area.  Internship often leads to hiring decisions.  I suggest you find internship at a renown company with a strong intern program so you can be mentored by an experience engineer or engineers. You need to discuss this when you interview with the company and try to understand what experience they can bring to you.

6. Summer research with professors: If you are interested in graduate programs, you should consider work with a professor or his/her group over the summer to see if you like conducting research.  Usually we pay students 29 hr per week with a salary around 10-12 $/hr for undergraduate students.  We sometimes will increase the hourly salary if you work more than 29 hours per week.  We don't like students who jump around projects or try to use this opportunity to fill in their gaps.  We don't expect undergraduate students to deliver results but we hope they treat the opportunity seriously and will learn from the experience.  

PHD (Notes to share for Students in MyGroup)

This is just a reference I made to my students.  

You will need to take the core courses from power systems and then select a few courses from outside ECE department.  I recommend the following from the perspective of my research group.  I recommend you take 3 courses in the first and second semester if you starts without a master degree. Then take 1 course and audit one plus 9 research credits or take 2 courses plus 6 research credits per semester so that you can do research projects and start to write papers.  

• 1. I recommend the following Seminar Series

1. Core courses: 

   1. • ECE550: Power System Operation and Control (Dr. Mesut Baran)

      • ECE551: Smart Electric Power Distribution Systems (Dr. David Lubkeman)

      • ECE552: Renewable Electric Energy Systems (Dr. Mesut Baran)

      • ECE516: Systems Control Engineering (Dr. Mo-Yuen Chow)

      • ECE534: Power Electronics 

        • Coursera: Power Electronics by Dr. Robert Erickson: Online Power Electronics

        • Introduction to Power Electronics lecture series: https://www.youtube.com/playlist?list=PLgwJf8NK-2e5Hnu82T1CYLZ8kbZs4Jx8x

        • Fundamentals of Power Electronics - Course Introduction (KatKimshow): https://www.youtube.com/watch?v=aE4UPFvafaM&list=PLmK1EnKxphikP6c9Yc9kGYO0kvrbEoWN8

      • ECE585: Utility Business (Dr. Wenyuan Tang)

      • ECE586: Communication SCADA Smart Grid (Dr. David Lubkeman) 

      • ECE581: Electric Power System Protection (Dr. Mesut Baran)

      • ECE592: Topic#40: Power System Transients Analysis (Dr. David Lubkeman) 

      • ECE 592-074 Data Analytics for Power Engineering (Arnie de Castro (adecast@ncsu.edu), Wenyuan Tang (wtang8@ncsu.edu).

      • ECE753: Computational Methods for Power Grid Operation and Planning  (Dr. Ning Lu)

      • ECE726: Advanced Feedback Control (Dr. Aranya Chakrabortty)

      • ECE736: Power System Stability (Dr. Aranya Chakrabortty)

2. Statistics: (at least 1)

   1. • ST511 (Exp Stat Bio Sc I) by Dr. X. Jessie Jeng

      • ST512 (Exp Stat Bio Sc II) 

      • ST501: Fundamentals of Inference I

      • ST502: Fundamentals of Inference II

      • ST503: Fundamentals of Regression

3. Computer Science and Engineering and Communication and Networks: 

• • NCSU Machine Learning Courses:

    •  CSC 522: ALDA first and then CSC591/791-001 Machine Learning for User-Adaptive Systems. by Dr. Min Chi

  • Online Machine Learning Lectures (Best Deep Learning Courses: Updated for 2019)

    • CS230 Stanford deep learning: https://www.youtube.com/watch?v=PySo_6S4ZAg&list=PLm4hZRdGlQQymAEbF4hQSx3GAKAaVbd1k

    • MIT Machine Learning -  Image Processing Convolution Neural network: https://www.youtube.com/watch?v=8rrHTtUzyZA

    • Stanford Vison Recognition: https://www.youtube.com/watch?v=vT1JzLTH4G4&list=PLf7L7Kg8_FNxHATtLwDceyh72QQL9pvpQ

    • Reinforcement learning by Shusheng Wang (in Chinese)

      • 1,2,3,4,5 (*****Very good for beginners)

    • Machine Learning Courses by Dr. Hung-yi Lee 李宏毅 (National Taiwan University) (in Chinese) (*****Very systematic and approximately 2-semester course layout)

    • Generative Adversarial Network (GAN): 01; 02; 03; 04; 05; 06; 07; 08; 09; 10

    • Auto-Encoder: (1/4): 01; 02; 03; 04

    • Transformer: https://youtu.be/4Bdc55j80l8 

    • Sequence Modeling with Connectionist Temporal Classification (CTC): https://distill.pub/2017/ctc/

    • Variational AutoEncoder

    • Machine Learning series. This series is very good.

    • Practical Machine Learning Tutorial with Python Intro p.1

    • Network Compression: 1 - 6

    • Reinforce Learning

      • • Reinforcement learning (Dr. Olivier Sigaud) (8 videos) : https://www.youtube.com/watch?v=e9GxQp-LONU&list=PLe5mY-Da-ksWV330WbfazLUyOuR59sers&index=2

        • Reinforcement learning (Dr. Hung-yi Lee ): 1 - 8

        • Reinforcement Learning (Dr. David Silver) (*****Very good for mastering the concepts and understand the development of the RL algorithms)

          • video: https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PLqYmG7hTraZDM-OYHWgPebj2MfCFzFObQ

          • Lecture Notes: https://www.davidsilver.uk/teaching/

        • DeepMind x UCL | Deep Learning Lectures | 1/12 | (by Thore Graepel, et. al) (*****Very good for mastering some advanced concepts and understand the latest development in machine learning algorithms)

    • video: https://www.youtube.com/watch?v=7R52wiUgxZI

      • Lecture Notes: https://deepmind.com/learning-resources/deep-learning-lecture-series-2020

    • Machine learning online courses offered by Dr. Andrew Nguyen

      • • Machine Learning

        • Deep learning online courses

    • Machine learning online courses offered by Professor Yaser Abu-Mostafa at CalTec 

    • Book: Python machine learning : unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics

    • Stanford CS229 I Machine Learning I Building Large Language Models (LLM model)

    • 
      

4. Operational Research

   1. • OR/ISE/MA505 – Linear Programming

      • OR705  – Large Scale Linear Programming

      • OR/MA/ST/ 706 – Nonlinear Programming

      • OR 709 Dynamic Programming 

• • ISE/OR 762  – Stochastic Simulation Techniques 

5. Industry Engineering 

   1. • IE723 (Production Planning, Scheduling and Inventory Control) by Dr. Tom Hodgeson

      • IE789 Soft Computing by DR. Fang.

      • ISE 505: Linear Programming

6. Math (Linear algebra and numerical analysis): 

   1. • Linear Algebra: online by 3Blue1Brown: https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab

      • MA 523, Matrix Analysis and Applied Linear Algebra I, by Dr. Carl Meyer

      • MA 723, Matrix Analysis and Applied Linear Algebra II, by Dr. Carl Meyer

      • MA 580 (Numerical Analysis I) by Dr. Ilse Ipsem

7. Control and Power Electronics

   1. • ECE536: Digital Control

      • ECE732: Dynamic Control of Electric Machines

      • ECE561: Embeded system

      • ECE534: Power Electronics

      • ECE792-1: Advanced Power Electronics

• 1. Writing class:  

     • ENG 626 Advanced writing for Empirical Research

8. Economics: micro-electronics

• • 1. Book: Principles of Microeconomics, 7th Edition (Mankiw's Principles of Economics) 7th Edition:  I also highly recommend the Chinese version of this book to all incoming Chinese PHD students.

9. Optimization: Power System Optimization Modeling in GAMS: Get access to the ebook Link from NC state library

10. Signal Processing and Communication

• • ECE 513 Digital Signal Process

  • ECE 570: Computer Networks (Communication network) 

  • ECE 547: Cloud Computing

  • Online Communication courses: Standard CS144 Introduction to Computer Networking

11. matlab tutorials

    1. matlab for training NN https://youtu.be/xOzh6PMk21I 

    2. matlab for quadratic optimization: https://youtu.be/U1sUtXxUuzs 

Courses Website

1. ECE 792 Moodle Site

2. ECE 451 Moodle Site

3. ECE 895 Moodle Site