Machine Learning is the study of how to build computer systems that learn from experience. It is a subfield of Artificial Intelligence and intersects with statistics, cognitive science, information theory, optimization, and probability theory. The course will explain how to build systems that learn and adapt using examples from real-world applications. The main topics include linear discriminant, neural networks, decision trees, support vector machines, unsupervised learning, and reinforcement learning.
Students will be able to:
Machine learning offers diverse and rewarding opportunities. You aspire to be a data scientist, machine learning engineer, AI research scientist, business intelligence analyst, or computer vision engineer, the field welcomes individuals with a passion for data and innovation.
