Program Overview

Data Science Program

The Data Science program offers a comprehensive curriculum that covers the tools and techniques for extracting knowledge from data. The program includes various courses that provide students with a solid foundation in data science.

Course Descriptions

• DATA 100: Introduction to Data Science: An introductory overview of the tools and techniques for extracting knowledge from data. Topics include Python basics, visualization, sampling, hypothesis testing, estimation, prediction, certainty assessment, and informed decision making.
• DATA 250: Computational Data Science: An intermediate course combining data, computation, and inferential thinking. Topics include data collection and cleaning, visualization, statistical inference, predictive modeling, and distributed computing.
• DATA 435: Predictive Analytics & Modeling: This course extends the ideas of linear models to data sets used in professional settings. Topics include linear and non-linear regression, logistic regression, discriminant analysis, principle component analysis, cross validation, and related topics.
• DATA 468: Big Data Analytics: This course covers methodologies and algorithms to transform big data into meaningful insights. Topics include Hadoop Ecosystem, Hadoop MapReduce, MongoDB, Spark basics, SparkSQL, and hands-on real-world applications.
• DATA 486: Special Topics in Data Science: A study of data science topics not ordinarily covered in the established courses. Prerequisite: consent of Data Science faculty.
• DATA 494: Independent Study: An independent study of a data science topic not covered elsewhere.
• DATA 495: Senior Capstone: Students design, develop, implement, and effectively communicate an original data science project.
• DATA 499: Internship in Data Science: On-the-job supervised experience and study dealing with applications of data science.

Program Requirements

• Pre-Requisites: Various courses have pre-requisites, such as DATA 100 for DATA 250, and MATH 202 and MATH 430 for DATA 435.
• Credits: Each course has a specific number of credits, ranging from 1 to 12 credits.
• Offerings: Courses are offered in the fall, spring, and summer semesters, with some courses offered at the department's discretion.

Academic Information

• Goal: The program aims to provide students with a solid foundation in mathematical and logical reasoning.
• Liberal Education Program: The program is part of the Liberal Education Program, which provides students with a broad-based education.
• Minnesota Transfer Curriculum: The program is also part of the Minnesota Transfer Curriculum, which allows students to transfer credits to other institutions.