Technical Elective Offered by the Department of Electrical and Computer Engineering (ECE)
This electrical and computer engineering-specific technical elective teaches students to apply the fundamentals of machine learning, artificial neural networks, and basic artificial intelligence. This class allows students to apply these concepts and methods to advanced problems relevant to advanced image processing, computer object recognition, and chatbot tools
The course prepares students for advanced graduate studies in in artificial intelligence and machine learning as well as lucrative positions at companies like:
- Intel
- Advanced Micro Devices, Inc. (AMD)
- NVIDIA
- Meta/Facebook
- Amazon
- Microsoft
Click here for the average salary for machine learning engineering within the United States.
Students who take this course will learn about:
- Probability, Maximum Likelihood, and Bayesian Classification and Estimation
- Gradient Descent-Based Optimization
- Advanced Linear Regression including Polynomial Curve Fitting
- Model Capacity, Regularization, and Over/Under Fitting
- Partitioning Datasets and Data Augmentation
- Unsupervised Learning, PCE, K-Means, t-SNE
- Feedforward Neural Network Structures
- Convolution and Mathematics Behind Deep Convolutional Networks
- Frameworks and Software for Neural Network Development
Faculty from The College of New Jersey have published multiple peer-reviewed research papers related to machine learning, including:
Mohammed Alabsi, Larry Pearlstein, Nithya Nalluri, Michael Franco-Garcia, and Zachary Leong. “Transfer learning evaluation based on optimal convolution neural networks architecture for bearing fault diagnosis applications.” Journal of Vibration and Control (2022).