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Aviation Data Science Lab


The USRA Aviation Data Science Lab is conducting research and education to advance national capabilities for applying machine learning and other data science techniques to grand challenges in aviation systems such as Urban Air Mobility. In collaboration with NASA’s Ames Research Center, academia and industry, a focus of the lab is on developing curriculum on aviation data sciences with academia for workforce development, as well as research and development to advance national needs for improved mobility of people and goods. Advances in Artificial Intelligence and Data Science are already positively impacting air transportation of goods and people, and have the promise for increased impact as the number of air vehicles grows exponentially with unmanned aerial systems and the amount of data grows in civil aviation with connected aircraft.

Advanced Aviation Data Science Course

This course teaches you advanced topics in machine learning such as detailed implementation of deep neural networks with application to the aviation domain. We will be using Sherlock, FAA, BTS, and FOQA data to build case studies throughout the course around applications of interest in predictive models for air traffic management, airport surface operations, and flight safety.

Duration: 12 weeks
Dates: March 2, 2021 - May 18, 2021
Time: Tuesday 10 am - 12 pm PST
Location: Microsoft Teams

Course will be taught in two phases:

  • Lecture and discussion on the topic of interest
  • Lab, with implementation of the methods learned on the real-world data using Python in Jupyter Notebook

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  • Linear Algebra
  • Python Programming
  • Introduction to Aviation Data Science




Introduction to Aviation Data Science Course 

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.

Duration: 12 weeks
Dates: March 10, 2020 - May 26, 2020
Time: Tuesday 10 am - 11:30 am PST

Course will be taught in four modules:

  • Data science basics
  • Supervised reasoning
  • Unsupervised reasoning
  • Dimensionality reduction and data visualization

We will cover three main areas of aviation data:

  • Airspace Operations
  • Surface Operations
  • 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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You can learn basics of this topic here: http://www.cs.cmu.edu/~zkolter/course/linalg/index.html.

Many online short-courses are available to learn the basics.

  • Linear Algebra
  • Basics of Python Programming




Seminar Series

USRA-NASA-Berkeley Aviation Data Science Seminar 2020.