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- Learning Objectives
- Jump start application of machine learning methods for trajectory prediction and use cases involving flight safety
- Potential Use Cases
- Flight safety, flight prediction, delay prediction, flight operations, predictive maintenance, aircraft monitoring
- Target Audience
- INTERMEDIATEData Scientists interested in aerospace verticals, flight analysts, operations research analyst in the aerospace verticals

Go through the following **annotated items** *in order*:

ARTICLE 1. IATA article on air passenger demand forecasts

- Why are developments and advanced analysis for flight safety necessary ?

10 minutes

ARTICLE 2. The future of the national airspace system

- What is the current state of the art and the future of air transportation systems that are (or will be) implemented ?

10 minutes

ARTICLE 3. Base of aircraft data: conventional approach to flight prediction

- What is the conventional physics based approach to trajectory prediction ?

10 minutes

PAPER 4. Flight trajectory prediction using deep generative convolutional recurrent neural networks approach

- How can we leverage deep learning in trajectory prediction ?

60 minutes

REPO 5. Deep trajectory prediction

- How to implement deep learning methodologies for trajectory prediction ?

120 minutes

PAPER 6. Introduction of uncertainty using Bayesian methods in flight trajectory prediction

- How can we include uncertainty in a manageable manner in flight trajectory predictions ?

60 minutes

VIDEO 7. Bayesian uncertainty integration with trajectory prediction explained

- How can we implement Bayesian uncertainty analysis and LSTMs for trajectory prediction ?

20 minutes

OTHER 8. Historic flight dataset

- Where can I access historic data to develop and test my methodologies ?

10 minutes

Previewing stream ** ML in Aerospace**

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