Semester.ly

Johns Hopkins University | EN.550.383

Scientific Computing with Python

4.0

credits

Average Course Rating

(3.4)

In this course, we will study numerical methods, and scientific computing using the Python language. We will discuss topics in numerical analysis, such as equation solving, differential equations, interpolation, integration etc. We will also introduce image analysis techniques such as filtering, denoising, inpainting, and segmentation. We will discuss core computer language concepts, algorithms, and data-structures using Python. No previous experience with computer programming is needed.

Spring 2015

Professor: Cristian Lalescu

(3.4)

Students who took this class found the course material to be highly useful for their course of study and applicable to a range of practical scenarios. Many students, however, found that the professor and the curriculum presumed familiarity with programming, coding, and math skills that are not listed among the prerequisites. Students were unclear as to their expectations from week to week, and suggested that a more structured syllabus and presentation of material would have been helpful. Prospective students should have working familiarity with calculus and linear algebra, as well as some prior experience programming and working with code, and be prepared to do some self-learning if material is unfamiliar.