University at Buffalo 3 credits Electrical Engineering
Probability and stochastic processes are fundamental to understanding uncertainty and dynamics in science and engineering, making them central to modern life. This course offers an in-depth overview of advanced concepts in probability theory and their practical applications. Students will develop powerful analytical tools that form the foundation for further study and research in areas such as communication, quantum computing, machine learning, and other emerging fields. Core topics include Markov chains, estimation, hypothesis testing, and concentration of measure results such as the Law of Large Numbers, the Central Limit Theorem, and Hoeffding’s inequality. By the end of the course, students will gain the skills and intuition to model, analyze, and reason about complex probabilistic systems, preparing them to engage with the challenges and innovations that drive today’s technological world.
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