CIVIL-459 / 6 credits

Teacher: Alahi Alexandre Massoud

Language: English


Summary

Self-driving cars, delivery robots, or self-moving segways. Most of these AI-driven transportation systems rely on four pillars: 1-Sensing, 2-Perceiving, 3-Predicting, and 4-Acting steps. Students will learn the fundamentals behind these four pillars, i.e., the technology behind autonomous vehicles.

Content

Keywords

Deep Learning, Autonomous Vehicle, Artificial intelligence, Machine learning, Self-driving car

Learning Prerequisites

Required courses

Fundamentals in Analysis, Linear algebra, Probability and Statistics.

Programming skills.

Learning Outcomes

By the end of the course, the student must be able to:

  • Define the fundamental steps behind an AI-driven system
  • Design the building steps of an autonomous vehicle
  • Implement an algorithm for each step
  • Explain and understand the challenges and ethical impacts

Teaching methods

Ex cathedra

Assessment methods

 Lab projects (in group): 30%

Midterm: 30%

Final project (in group): 40%

Prerequisite for

"Le contenu de cette fiche de cours est susceptible d'être modifié en raison du covid-19"

 


 

In the programs

  • Semester: Spring
  • Exam form: During the semester (summer session)
  • Subject examined: Deep learning for autonomous vehicles
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 4 Hour(s) per week x 14 weeks
  • Semester: Spring
  • Exam form: During the semester (summer session)
  • Subject examined: Deep learning for autonomous vehicles
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 4 Hour(s) per week x 14 weeks
  • Semester: Spring
  • Exam form: During the semester (summer session)
  • Subject examined: Deep learning for autonomous vehicles
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 4 Hour(s) per week x 14 weeks
  • Semester: Spring
  • Exam form: During the semester (summer session)
  • Subject examined: Deep learning for autonomous vehicles
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 4 Hour(s) per week x 14 weeks
  • Exam form: During the semester (summer session)
  • Subject examined: Deep learning for autonomous vehicles
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 4 Hour(s) per week x 14 weeks

Reference week

 MoTuWeThFr
8-9     
9-10     
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