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.
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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.
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.
As the number of air vehicles grows exponentially with unmanned aerial systems and the amount of data grows exponentially in civil aviation, the future holds more promise for a greater impact from advanced tools and techniques in data science and AI. This Spring, learn from experts in government, industry, and academia in a 12-seminar series, sponsored by USRA and UC Berkeley with NASA Ames Research Center.
USRA institutes and programs will celebrate USRA’s 50th anniversary on March 12, 2019. USRA was founded on March 12, 1969 in Washington, D.C. as a private, nonprofit corporation under the auspices of the National Academy of Sciences.
University Space Research Association NAMS staff received excellence awards at the 2018 Ames Contractor Council Excellence Award Ceremony. The award recipients were acknowledged at the ceremony by Ames Center Director Dr. Eugene Tu and were nominated by Dr. David Bell, Director of RIACS and NAMS Chief Technologist.