Data science skills are highly valued in the job market and most businesses are heavily investing to develop their analytics capabilities. This course adopts an experience-based learning approach and introduces the practice of data science to Katz graduate students. The course will emphasize the acquisition of skills such as (1) the use of a programming language (R, Python, etc.) to assemble, clean, and analyze data sets, (2) analytical and text-processing procedures for answering business questions, and (3) visualization and presentation of data-driven results for evaluation of business goals. The primary mode of learning will be through hands-on exercises involving real-world data used to make business decisions. For example, students will make use of the datasets and scripts used in data science competitions (e.g., Kaggle). Although no prior programming experience is required to enroll in the course, students should expect intensive out-of-class readings and practice sessions to get the most out of this course.
Prerequisite(s): BQOM 2401 Statistical Analysis