INFO 2646 - Introduction to Data Science

4.5 Credits

This course provides an overview of data science, covering the broad array of fundamental challenges in and methodologies for working with big data. Students will be introduced to the scientific programming environment, as well as the key theoretical concepts of both programming and statistical analysis. Specifically, this introductory course is designed to be integrative across core areas of data science, including statistics, data mining, machine learning, and data visualization. Students will acquire a working knowledge of data science through hands-on projects in a variety of business, engineering, social sciences or life sciences domains.

Pre/Corequisite: (1) MATH 1410 (or higher)

Lecture Hours: 4.5
Lab Hours: 0.0
Internship Hours: 0.0
Clinical or Practicum Hours: 0.0

Course Objectives

Understand problems solvable with data science and the data science project lifecycle
Collect, clean and manipulate data from different sources
Write programs in R
Visualize data and perform exploratory data analysis
Understand the basics of:
1. Clustering
2. Classification
3. Regressions
Understand the basics of:
1. Machine learning
2. Neural networks

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