Course Description
An introduction to data science with an emphasis on conceptual understanding and interpretation. Surveys various statistical techniques for gaining insights about data. Topics include data visualization, using models to understand data, classification, and other machine learning techniques. Explores ethical considerations in data science. Students will learn to use basic computational tools for data exploration.
Athena Title
Introduction to Data Science
Semester Course Offered
Offered fall and spring
Grading System
A - F (Traditional)
Course Objectives
After successful completion of this course, students will be able to: - Utilize common computational tools for data science. - Explain what types of questions can and cannot be answered from a given dataset. - Employ appropriate visualization techniques to gain insight into data. - Explain what a model is and how models are fit to data. - Use models for simple prediction problems. - Assess the validity of simple models. - Describe supervised and unsupervised learning methods for making predictions. - Understand the limitations of data science methods as tools for prediction and decision making. - Understand ethical issues surrounding data science.
Topical Outline
Introduction: Sources of Data, Data Collection, and Types of Data Understanding the Dataset Importing and Exporting Data in Python Basic Insights from Datasets Data Visualization: Importance of data visualization Univariate plots Bivariate plots Using Models to Understand Data: What is a model? Conceptual overview of model fitting Using models for prediction Assessing the model What can go wrong Classification - supervised vs. unsupervised: An overview of classification Why not linear regression? Comparison of different classification methods Some classical examples of Supervised and Unsupervised learning Broader Issues: Role of data in decision making Communication of results into actionable information Accuracy versus fairness Privacy and security Legal issues surrounding data
General Education Core
CORE III: Quantitative ReasoningSyllabus