C S 180
Download as PDF
Introduction to Data Science
Computer ScienceCollege of Computational, Mathematical, & Physical Sciences
Course Description
This course is a broad, interdisciplinary look at the field of data science, and how to derive insight from data. It will develop technical skills (including some python programming, statistics, linear algebra, machine learning, data cleaning and visualization) as well as data literacy (mental frameworks for decomposing data science problems, critical thinking about potential conclusions of an analysis, and potential pitfalls of overreliance on unreliable data).
When Taught
Fall and Winter
Min
3
Fixed/Max
3
Fixed
3
Fixed
0
Other Prerequisites
CS 110 or equivalent prior programming experience
Recommended
Prior programming experience should include statements, variables, control flow (if/while), and functions
Title
Derive Insight
Learning Outcome
Students will be able to use state-of-the-art data science oriented languages and toolkits to derive insight from data. This process is spiritually strengthening as students learn to discern truth and hidden patterns within complex information.
Title
Think Critically
Learning Outcome
Students will be able to think critically about conclusions drawn from data and its analysis. This rigorous evaluation of evidence is intellectually enlarging, training the mind to look beyond surface-level assumptions.
Title
Apply principles and methodologies
Learning Outcome
Students will be able to apply general data science principles and methodologies to novel data science problems. This adaptability fosters a foundation for lifelong learning, ensuring students can continue to solve evolving problems throughout their careers.
Title
Solve problems
Learning Outcome
Students will be able to combine ideas from mathematics, statistics, machine learning, and computer science to solve data science problems. The synthesis of these diverse fields is intellectually enlarging and prepares students to use their talents in professional and community service.
Title
Build predictive models
Learning Outcome
Students will build basic predictive models. The creation and refinement of these models is a character building exercise, requiring integrity in data handling and a commitment to producing honest, reliable results.
