CSCI 6344 Introduction to Data Science
This course provides an introduction to computational and statistical approaches to analyzing data. This Data Science course is designed to provide a comprehensive introduction to the field of data science. The course covers a wide range of topics including data and distributions, statistical inference, assessing pairwise relationships, and machine learning. In the first part of the course, students will learn about the basics of data and distributions, including measures of central tendency and variability, probability distributions, and statistical tests. They will also learn how to visualize data using plots and charts, and how to use statistical software to analyze data. The second part of the course focuses on statistical inference, including estimation and hypothesis testing. Students will learn about sampling distributions, confidence intervals, and p-values, and how to use these concepts to make inferences about populations based on samples. In the third part of the course, students will learn about assessing pairwise relationships, including correlation and mutual information. They will learn how to use these techniques to examine the relationship between two or more variables. Finally, the course concludes with an introduction to machine learning. Students will learn about the various types of machine learning, including supervised and unsupervised learning, and will explore the use of machine learning algorithms for prediction and classification.
Offered
Every other Spring