Scientific Programming in Python (361-0-01)

Instructors

Suzan van der Lee
847/491-8183
Tech F494
Office Hours: By appointment

Meeting Info

Technological Institute F491: Tues, Thurs 9:30AM - 10:50AM

Overview of class

Emphasis on analysis of authentic data and coding (programming) in Python from scratch, in a standard Unix computing environment. Beyond the common aspects of coding, we touch upon visualization, data fitting, solving equations, and tidbits of astro-, bio-, and geo-physics as well as parallel programming. The course is predominantly taken through self-paced, extensive, graded tutorials, called quizorials, inside and outside of the classroom. Students complete a final coding project that is relevant to their research or interests, individually or in pairs.

Continuing exercises will build familiarity and core strengths while final projects illustrate the computational research process from raw data or theory to somewhat polished "research product" and inspire development, critical thinking, creativity, persistence, and innovation.

This course bears graduate credit.

No prior programming experience is needed.

Office hours will be offered both online and in person.

Registration Requirements

No prior programming experience is needed.

Teaching Method

Flipped classroom, complete modules at reasonable pace, solve problems

Evaluation Method

Quizorials and final project

Class Materials (Suggested)

Optional: A Primer on Scientific Programming with Python by Hans Petter Langtangen, edition 5; ISBN 9783662498866; Price is approx. $80 new / $40 rental. Free online access to this book through NU Libraries: https://link.springer.com/book/10.1007/978-3-662-49887-3.

Class Attributes

Empirical and Deductive Reasoning Foundational Dis
Formal Studies Distro Area