A.I. and M.L. in Space 
Intermediate

Certificate:
 in A.I. and Machine Learning in Space - Intermediate

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Alessandro is a graduate in Space Systems Engineering at Delft University of Technology, currently working as a Systems Engineer at Airbus UK. Expert in stress engineering and aspiring futurist, with more than ten years of work experience in aeronautical companies in several countries, he has led data analytics projects aimed at the optimization and tailoring of maintenance programs. Member of INCOSE for several years, he presented at ASEC2014 on decision making algorithms in the sport business. A Chartered Engineer from the Royal Aeronautical Society, he is passionate about refining his skills by finding new ways to improve team work with new paradigms based on professional fulfillment, nurturing of talents and democratization of niche technologies. LEGO builder and drone pilot, he enjoys volunteering work as STEM ambassador and practicing mindfulness.

Certificate

At the end of the course, the participants receive a

 

Certificate in Artificial Intelligence and Machine Learning in Space - Intermediate

Overview

Get your certificate at the end of the course.

 

With the term Artificial Intelligence (A.I.) engineers and scientists include the set of techniques that allow computers able to work in an autonomous way. These computers are programmed by humans. As a result they learn how to behave under specific conditions. Nevertheless we are far away from having computers that are able to interpret situations autonomously and take independent decisions if not thought about the specifically.

One successful approach to Artificial Intelligence is through Machine Learning (ML),

ML is based on the principle of "training itself": the machine processes a basic algorithm which becomes quickly more elaborated and thanks to the data processing over time, the algorithm is able to adjust and improve itself. The machine simulate the human behaviour by developing artificial neural networks. The "learning" process can be supervised or unsupervised. In the first case (supervised process) data are fed into they system until it is able to recognize autonomously the solution. In the second case (unsupervised process) the network is able to find the structure autonomously.

 

Machine Learning is a complex world, which includes numerous techniques, such as Deep Learning, which allows image recognition.

These techniques are growing very fast in space applications. Both the Space Segment and the Ground Segment benefit from the usage of A.I. and M.L. The more satellites we launch in space, the higher is the need for them to be "intelligent". Ground applications require the use of A.I. and M.L. for example when dealing with Big Data, their processing and their dissemination to the end users.

When:  9th October 2021

Time:   16:00 to 19:30 CEST

Length: 4 Hours

Modes of Attendance: Online

Language: English

Registration Fee: 179 Euros

Program Overview:

The course Artificial Intelligence and Machine Learning in Space is a 4 hours course focuses on the fundamentals of A.I. and M.L. and the theory behind it: the logic, the development, improved techniques and solutions and  the way that the Space Sector makes usage of these applications to improve the quantity and quality of the deliverables. 

Program Details:

Welcome

 

Ice-braker interactive question(s)

1. ARTIFICIAL INTELLIGENCE (lesson 40 min, test 10 min)

1.1. Artificial life and applications

1.2. Expert systems and their components

1.3. Robotics and Human-AI cooperation

 

 

Break 10 min

 

Interactive question

2. MACHINE LEARNING AND ARTIFICIAL NEURAL NETWORKS (lesson 40 min, test 10 min)

2.1. Understanding the variables at play (big data)

2.2. How to train your AI

2.3. The importance of optimization

 

Break 10 min

Interactive question

 

3. A SYSTEMS ENGINEERING APPROACH (lesson 40 min, test 10 min)

3.1. What is a system?

3.2. Spacecraft Systems Architecture

3.3. Set-up and management of expert systems

 

Break 10 min

Interactive question

4. APPLICATIONS (lesson 45 min, test 15 min)

4.1. Classification

4.2. Prediction

4.3. Interactive exercise

 

Why Choose the Course in Artificial Intelligence and Machine Learning in Space?

  • The artificial intelligence specialist hiring has grown 74% in the last four years (Forbes

  • Participants acquire a complete overall knowledge about the topic as well as specific applications in the Space Sector.

  • Networking: You have the opportunity to network and learn from experts in the A.I. and M.L. sector.

  • Receive answers to your questions about business development in the A.I. and M.L. sector.

  • The course is open to all passionate individuals who wish to learn about A.I. and M.L. No prerequisite is needed to register to the course.

Learning Objectives:

At the end of the course the Student will have:

- Learnt about the theory of Artificial Intelligence and Machine Learning

- Learnt about A.I. and M.L. applications logic and propagation to other sectors

- Received the inputs to develop new ideas about A.I. and M.L. applications

- Asked the experts about individual questions related to A.I. and M.L.

- Established good contacts with experts in the A.I. and M.L. sector 

Lecturer: