5 courses with the subject DATA, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
DATA 131Foundations of Data Analytics I
3 sem. hrs. In an increasingly data-driven world, everyone should be able to understand the numbers that govern our lives. Whether or not you want to work as a data analyst, being “data literate” will help you in your chosen field. In this course, you’ll learn the core concepts of inference and data analysis by working real data. By the end of the term, you’ll be able to analyze large datasets and present your result.
3 sem. hrs. This course is intended as a continuation of Foundations of Data Analytics I. In this course, you’ll learn how Data Analytics are applied within the workforce. Particular attention will be paid to the role of the Data Scientist or Analyst, machine learning and the applications of Big Data. By the end of the term, you will be able to design and execute a range of data-driven experiments.
DATA 333Principles and Techniques of Data Analytics I
3 sem. hrs. Data Analytics combines data, computation and inferential thinking to solve challenging problems and understand their intricacies. This class explores key principles and techniques of data science, and teaches students how to create informative data visualizations. It also explores particular concepts of Linear Algebra which are central to Data Science.
DATA 334Principles and Techniques of Data Analytics II
3 sem. hrs. Data Analytics combines data, computation and inferential thinking to solve challenging problems to thereby better understand the world. This class explores key principles and techniques of data science, including quantitative critical thinking and algorithms for machine learning methods. It will also introduce students to the ways in which data analytics is deployed in healthcare, marketing, political science, criminal justice, and other fields.
3 sem. hrs. This course is a capstone project in which students are asked to work through a full data science workflow on a set of real data drawn from sports, politics, business or public health. This course exists to prepare students for the kind of work they will do on Data Science or Analytics teams, and such, also features an emphasis on interviewing for jobs in the space and communicating results to stakeholders.
