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 100Introduction to Data Science1
Offered Either Fall or Spring; Lecture hours:3,Other:1.5An introduction to data science where students develop their data acumen and learn techniques for analyzing and modeling data. The course covers the entire data analysis process and students develop a reproducible analysis workflow in R. No prior statistics or computing knowledge is expected. Not open to students who have taken ANOP 330, CSCI 349, DATA 250 or STAT 230.
Offered Either Fall or Spring; Lecture hours:3Students will examine AI's foundations, historical development and how it mirrors and diverges from human cognition and learning. Through experimentation and reflection, they will explore the computational, ethical, environmental and societal impacts of AI while developing personal strategies to evaluate its capabilities and protect their own learning in an AI-obsessed world. We will learn by reflecting and doing. No Junior/Senior. Crosslisted as HUMN 101.
Offered Either Fall or Spring; Lecture hours:3,Other:1A dynamic introduction to linear methods in data science and AI. The course uses real world problems to both motivate and explore essential concepts from linear algebra. Working directly with real data, students will learn how to use the powerful linear toolkits in Python and understand how fundamental problems in AI are modeled and solved with linear methods.
Offered Either Fall or Spring; Lecture hours:3An introduction to the concepts, core techniques and software of data science; emphasizing both data science principles and methods. Topics may include: computational libraries for data science and visualization; statistical and machine learning algorithms for regression, classification and clustering. Prerequisites: CSCI 204 and MATH 216 or STAT 216 or MATH 227 or STAT 227.
Offered Alternating Fall Semester; Lecture hours:3Experiential learning course with collaborative data focused projects. Students will learn about and engage with important data science topics. Advanced statistical software will be used. Prerequisites: (STAT 216, STAT 227, ANOP 102, PSYC 215 or ENGR 226) and (STAT 230, CSCI 203 or ANOP 203) and (STAT 217, CSCI 349, ANOP 330, or MECH 484). Equivalent to STAT 306.
