Semester.ly

Johns Hopkins University | EN.580.200

Introduction to Scientific Computing in Bme Using Python, Matlab, and R

3.0

credits

Average Course Rating

(3.91)

This course is an introduction to scientific programming and computing designed for first-year students. The aim is to develop core computer skills required to succeed in research. Programming projects are drawn from current biomedical applications within BME. Emphasis is on algorithm development, large scale data analysis, and effective visualization of results, using MATLAB, Python, and R. Prior programming experience is not required.

Spring 2013

(4.1)

Spring 2014

(4.06)

Spring 2015

(3.57)

Spring 2013

Professor: Michael Beer

(4.1)

The best aspects of this course included the fundamental components of computer science languages, the comprehension and ease with which the instructor introduced the material, the helpful and relevant textbook utilized, and the comprehensive content that helped familiarize students with a variety of programming languages. One student felt as though the instructor took too long to post grades online. Another student felt that assignments not given from the textbook were often unclear and difficult to understand. Suggestions included making a conscious effort to distribute the work evenly throughout the semester and incorporating more lessons with MATLAB. Prospective students should know that

Spring 2014

Professor: Michael Beer

(4.06)

This course was solid introduction to programming and concepts of algorithms. It was beginner friendly, and many students felt like they progressed at a fairly fast pace. The assignments given tested students’ knowledge and al owed them to practice the language confidently. But there was a lot of work involved in this course, and some students said that the professor kept trying to relate the class to Biology. In addition, grading was completed late, there wasn’t enough time spent on R, the class seemed a bit rushed, and the syl abus wasn’t fol owed. Suggestions for improvement include: more focus on Matlab and R, a section TA, less course work, and more help sessions for students. Prospective students should prepare for tons of work and should have some computer science background.

Spring 2015

Professor: Michael Beer

(3.57)

The best aspects of this course included the solid introduction to programming with Python and MATLAB and the rewarding final projects. While the frequent and time consuming homework assignments were good practice, many students complained that the workload was overwhelming. This compromised the quality of student work as well as that of the feedback they received. The lectures themselves could have been more engaging, and the textbooks often proved more useful than the lectures, according to some students. While it is not necessary, prospective students may benefit from some prior programming experience. Prospective students should be ready to adhere to a strict schedule of assignment deadlines throughout the semester. 33