This course develops computational proficiency in Python for statistical analysis and data science. It covers programming fundamentals, data structures, and control flow, followed by data processing, visualization, and statistical inference using modern libraries. Students implement hypothesis testing, regression concepts, and simulation techniques including random number generation and MCMC methods. Emphasis is placed on integrating statistical theory with computation to solve real-world problems, fostering analytical thinking, reproducibility, and research-oriented skills in data-driven environments.
- BCM Teacher: Stephy Thomas
- BCM Teacher: Admin User