Data Science

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Associate Professors: Marcus Birkenkrahe
Assistant Professor: Pietro Dall'Olio

Data is being generated at all times, arriving from multiple sources at an incredible rate. Nearly every device connected to the internet is generating data, and those capable of analysis and study of it are increasingly in demand. The ongoing generation of “big data” has resulted in a new job market: business leaders, scientists, engineers, and leaders from all walks of life have realized that they need scientists with the knowledge and ability to analyze, and understand the implications of the data and then communicate their findings. In addition to the data that is being constantly generated through modern commercial use of the internet, an abundance of data has been in existence for some time. The proper study and understanding of the implications of this data is increasingly important.

The Lyon College Data Science program will provide students with the theoretical background and initial problem-solving experiences focusing on three general broad areas: science, business and economics, and social sciences and humanities.

NOTE: To graduate with a Bachelor of Arts or Bachelor of Science degree from Lyon College, students must successfully complete a minimum of 120 semester credit hours comprised of our required Core curriculum (44-48 hours), the requirements of at least one major (credit hours vary per major), and a selection of our Liberal Arts electives. They must also earn at least a 2.00 cumulative grade point average for all work taken at Lyon College and a 2.00 cumulative grade point average in their major, minor, and concentration.

Degrees

Courses

DSC 105: Introduction to Data Science

Class Program
Data Science
Credits 3

This course provides a general overview of the common topics in the data science domain. Students are introduced to data collection, data engineering, machine learning algorithms and packages, data visualization techniques and related programming tools and frameworks.

Prerequisites

CSC 100 or CSC 109 or CSC 115, and MTH 115 or MTH 290

DSC 205: Introduction to Advanced Data Science

Class Program
Data Science
Credits 4

Data collection, data engineering, machine learning algorithms and packages, data visualization, and related programming tools and frameworks. These topics are covered in DSC 105, but here they will be discussed in more depth, and projects will reflect real world challenges. In addition, data mining techniques and more advanced machine learning algorithms will be introduced. In some cases, the statistical concepts behind some of the algorithms will be discussed. Projects may involve text and image classification tasks, developing regression models, etc.

Prerequisite Courses
DSC 105
Prerequisites

Or permission of the instructor.

DSC 302: Data Visualization

Class Program
Data Science
Credits 3

This course presents the art and science of turning data into readable graphics. We’ll explore the design and creation of data visualizations based on data available and tasks to be achieved. This process includes data modelling, data processing, mapping data attributes to graphical attributes, and strategic visual encoding. Students will evaluate the effectiveness of visualization designs and create their own data visualizations.

Prerequisites

CSC 100, or CSC 109, or CSC 115, or permission of the instructor.

DSC 305: Machine Learning

Class Program
Data Science
Credits 3

This course aims at providing mathematical explanations of the machine learning models discussed in DSC 105 and DSC 205. Topics include probability, probabilistic models, statistical concepts related to machine learning, and analysis of some of the popular machine learning models with the help of probability and statistics. Projects will reflect real world challenges and will aim at discovering how machine learning models work.

Prerequisites

DSC 105, DSC 205, CSC 265, or permission of the instructor.

DSC 401: Data Science Applications and Programming

Class Program
Data Science
Credits 3

This course will offer programming languages and techniques necessary to process and analyze data. Special emphasis will be on advanced use of Python and R languages to analyze datasets from a variety of disciplines and industries.

Prerequisite Courses
CSC 245

DSC 402: Data Science Capstone

Class Program
Data Science
Credits 3

Students will apply their data science knowledge and technology to a real world scenario. Students can accomplish this by working with a local businesses, acquiring data from governmental entities, or through an internship. The capstone will conclude with a final deliverable report and presentation to the business, government, or internship entity.