Educational Outreach

We offer the following graduate level courses, but all are co-listed with a corresponding undergraduate course (for senior level undergraduate students, or, for sophomore and junior level students with extraordinary talents who can apply by admission by special permission). Related courses in other Departments, Colleges and Schools complement these courses. For more information about them contact the CACMS Director. 

Name: CHEM 5510 - Computational Chemistry
Description: Classical and ab initio molecular dynamics are covered from theory to application. Students have access to high-performance computational resources and cover current topics in the field. Requisite knowledge in Undergraduate Physical Chemistry is assumed. Cross-listed with CHEM 4510.
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Name: CHEM 5580 - Molecular Informatics
Description: This course resides at the intersection between Chemistry, Biochemistry, and Data Science. The course covers fundamental concepts of Chemical and Biochemical Informatics and provides students with hands on experience in using computational tools to manipulate chemical and biochemical data. Students will learn fundamentals of data science, database management, data structure, data representation, data visualization, and data analysis as applied to Chemistry and Biochemistry. The course requires a basic understanding of programming but does not require extensive programming experience. Examples explored in class and in homework will be built using Python code within Jupyter Notebooks or Google Colab notebooks such that students can explore new topics while remaining focused on the underlying molecular concepts and computer methods which allow them to manage large amounts of molecular information and to find relationships between the structure and properties of molecules. Data mining approaches will be explored as will classification algorithms and chemical similarity analysis methods. Students will learn about the applications of cheminformatics in drug discovery, such as compound selection, virtual library generation, virtual high throughput screening which can check for potential molecules that have the potential to be developed into drugs. Note: While this course is not a pre-requisite for 4510 Computational Chemistry, CHEM 4640 AI in Chemistry and Biochemistry, or CHEM 4845 Molecular Modeling and Drug Design, the skills developed in this course will work synergistically with those courses and will allow you to get more from your experiences in those courses or from your experience in a research lab.
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Name: CHEM 5630 - Programming for Data Analysis in the Physical Sciences
Description: This course will be taught using live coding format (the instructor will code live in the classroom with the students). In this course, you will learn to process data using python scripts that you will write. Data include for example absorption spectra, protein pdb files, coordinate files. You will also learn how to use Python libraries and write functions (for example to create high resolution graphs). Finally, you will learn best coding practices, how to keep track of different versions of your code and share your code using Github. Cross-listed with CHEM 4630.
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Name: CHEM 5640 / 4640 - Artificial Intelligence in Chemistry and Biochemistry
Description: Artificial Intelligence (AI) changes every aspect of our lives. In this course, we explore AI and its applications from the perspective of a chemist/biochemist. The role of AI and the latest trends in modern chemistry and biochemistry will be taught. Students will learn how to connect modern AI techniques to their own research projects, using both experimental and computational data.
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Name: CHEM 5845 - Molecular Modeling and Computer-aided Drug Design
Description: Advanced course in biochemistry. An introductory course on modern molecular modeling techniques and their applications to computer-aided rational drug design. Cross-listed with CHEM 4845.
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