Pick the Right Course

CS 1110 is a 4 credit course designed for freshmen and sophomores. While it offers an introduction to computer programming concepts, it goes a lot deeper than that. It also emphasizes techniques of software developement and program design. On the other hand, it does not cover the use of specialized Python packages such as NumPy or Pandas. Depending on your needs, you may find that other classes are a better fit.

CS 1133: The Short Course

CS 1110 is not an ideal class for students who just want to learn a little Python. It involves a significant amount of work both in and out of class. Because of enrollment demand, CS 1110 no longer allows students to take the course S/U; this can be stressful for students who just wish to explore the material.

CS 1133 is a 2-credit course that covers the first half of CS 1110. It focuses on the basics in programming in Python, but does not include a lot of the computer science material in CS 1110. This course is also S/U and therefore a more forgiving experience.

CS 1112: Intro CS: Scientific Computing

CS 1112 is the primary alternative to CS 1110. Both courses are designed to prepare students for CS 2110 and future computer science courses. And both courses are taught in Python (if your goal is simply to learn some Python). The difference is in how they approach Python. CS 1110 emphasizes software application development, while CS 1112 is focused on applications for engineering and data science. CS 1112 does require a firm background in mathematics and at least one semester of calculus. If you are engineering student whose interests lie outside the digital major cluster (CS, ECE, ORIE, ISST), we recommend that you consider this course instead.

INFO 1300: Web Design & Programming

If you are shopping around for a “first course” to take in programming or computer science, it is worth examining some of the course offerings in the Information Science department.
INFO 1300 is a course on design and programming for the web. This course does not cover as many computer science concepts as either CS 1110 or CS 1112. However, it does an excellent job emphasizing design, and is one of the best courses available for this.

INFO 5001: Computing for Information Science

If you are a graduate student who needs to learn Python or computing, INFO 5001 is slightly more in-depth than CS 1133. While it is designed primarily for Information Science MPS students, it is open to other graduate students as well.

AEM 2840/5840: Python Programming for Data Analysis & Business Modeling

AEM 2840 is an introduction to programming with Python for students aiming to enter the world of business analytics. This class is not limited to learning Python; it also teaches how to use several tools for data analytics such as NumPy, MatPlotLib, Seaborn, Pandas, and Scikit. This is the preferred course for Dyson students.

EAS 2900: Computer Programming and Meteorology Software

EAS 2900 teaches Python programming, together with visualization techniques used in meteorology and climate science. This includes exposure to tools such as NumPy, Pandas, xArray, CartoPy, and MetPy. EAS 1310 is a prerequisite.

CEE/ENMGT 3101/5101: Introduction to Python for Engineering

CEE 3101 is a one credit course that focuses on libraries for scientific programming, such as NumPy, Matplotlib, SciPy and Pandas. It assumes that you know a little bit about programming and just want to learn some Python-specific tools.