This course teaches you fundamentals of reproducible data science and analytics, probabilistic reasoning & statistical inference, and machine learning to leverage data generated within the large scope of aviation and aeronautics. Course will be taught in four modules: (1) data science basics, (2) supervised reasoning, (3) unsupervised reasoning, and (4) dimensionality reduction and data visualization. We will cover three main areas of aviation data: (1) Airspace Operations, (2) Surface Operations and (3) Flight Safety. We will be using ATD-2, Sherlock, and FOQA data to build the case studies. Course is designed in two phases: (i) lecture and discussion: on the important topics in each module, and (ii) lab: with implementation of the methods learned on the real-world data using Python in Jupyter Hub. Evaluation will be based on a few individual assignments and a group project.
1 Linear Algebra, you can learn basics of this topic here:
2 Basics of Python Programming, many online short-courses are available to learn the basics.