Description: Survey of core algorithms for statistical computing in biostatistics. Topics include divide-and-conquer algorithms, random number generation, numerical integration, optimization, Monte Carlo methods, and the EM algorithm. Students learn to interpret computational results and implement statistical methods in R and Python, leveraging generative AI tools.
