Courses Details

BIOSTAT615: Ai-assisted Statistical Programming

  • Graduate level
  • Residential
  • Fall term(s) for residential students;
  • 3 credit hour(s) for residential students;
  • Instructor(s): Hyun Min Kang (Residential);
  • Prerequisites: None
  • 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.
  • Learning Objectives: this is not a new course
  • Syllabus for BIOSTAT615
KangHyun
Hyun Min Kang