Machine Learning

The Machine Learning track provides students with the tools and techniques for developing systems that improve their performance through data. Students study supervised and unsupervised learning, deep learning, reinforcement learning, and statistical modeling. Coursework emphasizes practical implementation using modern frameworks as well as theoretical underpinnings of learning algorithms. Machine learning has wide-ranging applications in speech recognition, predictive analytics, personalized medicine, cybersecurity, and artificial intelligence systems. By mastering these methods, graduates will be prepared to contribute to the rapid advancement of technologies that rely on intelligent data-driven decision-making.