History

CDS-Exchange is built upon the initial work done by the NSF-funded Computational and Data Science Curriculum Exchange (C2Exchange) that explored collaboration models for developing undergraduate computational and data science curriculum, minors, and certificates with low investment. The exchange approach is intended to minimize the faculty preparation time required to deliver new and updated courses; and increase the number of computational and data science courses offered at the participating institutions. The C2Exchange model leveraged national efforts to integrate computational and data science into the curriculum and applied distance learning technologies to enable stable computational and data science offerings at the academic institution partners. [NSF Grant 1829717] 

C2Exchange partners developed and shared the following courses.

• Computational Chemistry and Molecular Modeling: A 4-credit hour course including lectures and labs to introduce the concepts of computational chemistry and molecular modeling and their applications in chemistry and biology.

• Matrix Methods for Data Science and Machine Learning: Students learn advanced linear algebra topics necessary for organizing information, analyzing large data, exploring machine learning techniques to build models and solve problems.

• Introduction to Modeling and Simulation: This course infuses fundamental concepts of computational science into the undergraduate general education curriculum. It introduces the principles of modeling and simulation; progressive introduction of programming principles and skills using Python; application of programming skills to the solution of different classes of models. This is a 3-credit course with College Algebra as a prerequisite.