Explores variance reduction techniques in stochastic simulation, emphasizing the use of auxiliary random variables and sample averages to improve efficiency.
Explains the 2nd year curriculum, including progression conditions, retaking courses, credits, and options, emphasizing the importance of English proficiency and course selection.
Covers maps as key-value data structures, including querying, updating, and handling missing values, with practical examples like polynomial representation.
