Coursework
Foundations of Data Science
The hallmark of NCSSM's coursework in data science is Foundations of Data Science, offered since Fall 2020. This course introduces students to the key elements of working with data:
exploration and visualization,
statistical inference, and
prediction and classification
while also learning the Python programming language to complete these tasks. The curriculum is adapted from UC-Berkeley's wildly successful Data 8 course, taken by thousands of students each year in their undergraduate program.
NCSSM-Morganton
Every junior at NCSSM-Morganton is required to complete Foundations of Data Science in either the Fall or Spring semester. Students will have the opportunity to apply these essential skills and leverage the data science tools in unique data-enabled interdisciplinary courses in their senior year.
Data-ENabled Courses
In addition to Foundations of Data Science, NCSSM-Morganton students can take coursework within all of our academic departments that embed data science skills and tools, as well as thoughtful consideration into the ethical use of data, into their coursework.
Examples include:
Engineering & Computer Science
CS4250: Data Visualization
CS4320: Machine Learning
Humanities
HU4420: Digital Humanities
EN4400: AI in Science Fiction
HU4425: Data Ethics and Data Justice in the Age of AI
Mathematics
MA4260: Operations Research
MA4320: Linear Algebra with Applications
Science
PH4130: Computational Physics
NCSSM-Durham
Students at NCSSM-Durham have the option to complete Foundations of Data Science in either their junior or senior year. Students can then choose to complete other data science courses like Linear Algebra and Machine Learning or enroll in forum courses similar to those that have been offered in the past: Natural Language Processing and Sports Analytics.
NCSSM-Online and Connect
Students enrolled in the NCSSM-Online program or participate in the NCSSM Connect program have the ability to complete Foundations of Data Science. Students can also engage in computational science coursework that can leverage their data science knowledge to solve problems in discipline specific sciences, like chemistry, biology, and/or physics.