ESE 542 Statistics for Data Science: An Applied Machine Learning Course

Short Description

Learn a broad range of statistical and computational tools to analyze large datasets through a solid foundation of data science, statistics and machine learning to make data-driven predictions via statistical modeling and inference. Using case studies and hands-on exercises, practice and increase data analysis skills using Python to extract meaningful information from large datasets.

Portfolio Building Course

No

Pre-Requisites

CIT 592, Programming background, Basic Probability

Content

In this course, students will learn a broad range of statistical and computational tools to analyze large datasets. This course provides a solid foundation of data science, statistics and machine learning to make data-driven predictions via statistical modeling and inference. Using case studies and hands-on exercises, the student will have the opportunity to practice and increase their data analysis skills using Python. The objective of these case studies is to identify and implement appropriate modeling and analysis techniques in order to extract meaningful information from large datasets.

Course Offerings
  • Spring 2022 Victor Preciado
  • Summer 2022 Victor Preciado
Course Creators