Probabilistic Methods (PM)

Description

This course outlines a comprehensive path for learning and applying probabilistic methods to various real-world scenarios, equipping students with the theoretical knowledge and practical skills to leverage uncertainty and randomness in their professional activities. From the beginning, students will learn the fundamental concepts and mathematical frameworks of probability theory and develop proficiency in statistical reasoning and inference to analyse data and make informed decisions with insight into developing a mathematical understanding of probabilistic models and how they can be employed to interpret data, make predictions, and inform decision-making processes. Besides, in the tutorials and labs, students will gain hands-on experience through several coding assignments and exercises. Finally, student will participate in a project to apply probabilistic methods to model uncertainty and solve problems across various applications such as Monte Carlo simulations to tackle real-world challenges in technology, finance, and research.