Computational Methods of Scientific Programming

4-0-8 units · Undergraduate

Introductory subject exposes students to modern programming methods and techniques used in practice by physical scientists today. Emphasis on code design, algorithm development/verification, and comparative advantages/disadvantages of different languages (including Python, Julia and C/C++) and tools (including Jupyter, machine-learning from data or models, cloud and high-performance computing workflows). Students are introduced to and work with common programming tools, types of problems, and techniques for solving a variety of data analytic and equation modeling scenarios from real research: examination visualization techniques; basic numerical analysis; methods of dissemination and verification; practices for reproducible work, version control, documentation, and sharing/publication. No prior programming experience is required.