Computing and Data Science for Soft Materials Certificate

Program Policy Document:

Please see the Program Policy Document for more information.

Degree Requirements:

This Certificate requires at least 9 course credits as listed below.

Required Courses:

CHEG 848 - Computing and Data Science for Soft Materials Innovation Credit(s): 3

Restricted Elective(s):

CISC and ELEG Primary Discipline Elective:

Students in Computer Information Science or Electrical and Computing Engineering must complete three credits from any of the following graduate electives approved in their graduate program as their Primary Discipline elective course.

BINF 684 - Introduction to Machine Learning Credit(s): 3
CISC 642 - Introduction to Computer Vision Credit(s): 3
CISC 662 - Computer Systems: Architecture Credit(s): 3
CISC 681 - Artificial Intelligence Credit(s): 3
CISC 684 - Introduction to Machine Learning Credit(s): 3
CISC 879 - Advanced Topics in Architecture and Software Systems Credit(s): 3-12
CISC 882 - Natural Language Processing Credit(s): 3
ELEG 602 - Advanced Machine Learning Credit(s): 3
ELEG 817 - Large Scale Machine Learning Credit(s): 3
ELEG 845 - Modern Machine Learning Credit(s): 3

CISC and ELEG Secondary Discipline Elective:

Students in Computer Information Science or Electrical and Computing Engineering must complete three credits from any of the following electives as their Secondary Discipline elective course.

CHEG 647 - Molecular Modeling and Simulations of Soft Materials Credit(s): 3
CHEG 600 - Introduction to Science and Engineering of Polymer Systems Credit(s): 3
CHEG 818 - Scattering Methods for Soft Matter Credit(s): 3
CHEG 847 - Molecular Modeling and Simulations of Soft Materials Credit(s): 3
MSEG 631 - Organic Electronics: Design, Synthesis, and Applications Credit(s): 3
PHYS 661 - Data Science for Physical Scientists Credit(s): 3
PHYS 664 - Machine Learning for Time Series Analysis Credit(s): 3

MSEG, BMEG, and CHEG, CHBC Primary Elective course:

Materials Science and Engineering, Biomedical Engineering, Chemical & Biomolecular Engineering, Chemistry & Biochemistry students must complete three credits from any of the following graduate electives approved in their graduate program as a Primary Discipline elective course.

CHEG 600 - Introduction to Science and Engineering of Polymer Systems Credit(s): 3
CHEG 647 - Molecular Modeling and Simulations of Soft Materials Credit(s): 3
CHEG 818 - Scattering Methods for Soft Matter Credit(s): 3
CHEG 847 - Molecular Modeling and Simulations of Soft Materials Credit(s): 3
MSEG 628 - Macromolecular Design & Bioconjugations Credit(s): 3
MSEG 631 - Organic Electronics: Design, Synthesis, and Applications Credit(s): 3
MSEG 660 - Biomaterials and Tissue Engineering Credit(s): 3
MSEG 817 - Composite Materials Credit(s): 3
MSEG 835 - Principles to Polymer Physics Credit(s): 3

MSEG, BMEG, and CHEG, CHBC Secondary Elective course:

Materials Science and Engineering, Biomedical Engineering, Chemical & Biomolecular Engineering, Chemistry & Biochemistry Students must complete three credits from the following restricted elective list as a Secondary Discipline elective course.

BINF 684 - Introduction to Machine Learning Credit(s): 3
CHEG 647 - Molecular Modeling and Simulations of Soft Materials Credit(s): 3
CHEG 847 - Molecular Modeling and Simulations of Soft Materials Credit(s): 3
CHEG 861 - Data Science for Chemical and Biomolecular Engineering Credit(s): 2
and
CHEG 807 - Advanced Modeling, Analysis, and Acquisition of Data Credit(s): 2
or
CHEG 860 - Process Systems Engineering: Mathematical Modeling and Optimization Principles Credit(s): 2
CISC 684 - Introduction to Machine Learning Credit(s): 3
CISC 882 - Natural Language Processing Credit(s): 3
ELEG 602 - Advanced Machine Learning Credit(s): 3
PHYS 661 - Data Science for Physical Scientists Credit(s): 3
PHYS 664 - Machine Learning for Time Series Analysis Credit(s): 3

Internship / Teaching Workshop:

Graduate students will also complete a career pathway requirement after completion of the course requirements. Students interested in pursuing industry or national lab work will complete a summer internship in either industry or national lab. Students interested in pursuing careers in academia will complete a summer teaching workshop.

UNIV 554 - Graduate Intership Semester Credit(s): 0