A sophomore course in Engineering Computations at the George Washington University, Mechanical and Aerospace Engineering department. The local course number is MAE 2117.

This is a full course re-write for Fall 2017, by Prof. Lorena A. Barba and doctoral student Natalia C. Clementi.

The course consists of a set of somewhat self-contained Modules, addressing an area of application or skills in computing. Each module is made up of four or five lessons, written as a Jupyter notebook. We use Python as the programming language.

We take inspiration in the ideas of Seymour Papert about computational thinking. In particular, we want to design a course that adheres to Papert's Power Principle:

What comes first, "using" or "understanding"? The natural mode of learning is to first use, leading slowly to understanding. New ideas are a source of power to do something.

Module 1: Get data off the ground

1. Interacting with Python
2. Play with data in Jupyter
3. Strings and lists in action (MAE Bulletin example)
4. Play with NumPy arrays
5. Linear regression with real data

Module 2: Take off with stats

1. Cheers! Stats with beers
2. Seeing stats in a new light
3. Lead in lipstick

Module 3: Fly at change in systems

Module 4: Land on vector spaces

(c) 2017 Lorena A. Barba, Natalia C. Clementi. All content is under Creative Commons Attribution CC-BY 4.0, and all code is under BSD-3 clause. We are happy if you re-use the content in any way!