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Self-Driving Cars
Coursera
Specialization
Unknown

Self-Driving Cars

University of Toronto

Provides advanced understanding of engineering in self-driving cars, with practical projects using CARLA simulator and real autonomous vehicle data.

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About this Course

Be at the forefront of the autonomous driving industry. With market researchers predicting a $42-billion market and more than 20 million self-driving cars on the road by 2025, the next big job boom is right around the corner. This Specialization gives you a comprehensive understanding of state-of-the-art engineering practices used in the self-driving car industry. You'll get to interact with real data sets from an autonomous vehicle (AV)―all through hands-on projects using the open source simulator CARLA. Throughout your courses, you’ll hear from industry experts who work at companies like Oxbotica and Zoox as they share insights about autonomous technology and how that is powering job growth within the field. You’ll learn from a highly realistic driving environment that features 3D pedestrian modelling and environmental conditions. When you complete the Specialization successfully, you’ll be able to build your own self-driving software stack and be ready to apply for jobs in the autonomous vehicle industry. It is recommended that you have some background in linear algebra, probability, statistics, calculus, physics, control theory, and Python programming. You will need these specifications in order to effectively run the CARLA simulator: Windows 7 64-bit (or later) or Ubuntu 16.04 (or later), Quad-core Intel or AMD processor (2.5 GHz or faster), NVIDIA GeForce 470 GTX or AMD Radeon 6870 HD series card or higher, 8 GB RAM, and OpenGL 3 or greater (for Linux computers)

What You'll Learn

  • Understand architecture and components of self-driving car software
  • Implement object detection, localization, planning, and control methods
  • Utilize multi-sensor data to build realistic environmental models
  • Demonstrate proficiency with CARLA and Python programming

Prerequisites

  • Prior hands-on experience with core concepts
  • Comfort applying main tools independently

Instructors

S

Steven Waslander

Associate Professor

J

Jonathan Kelly

Associate Professor

Topics

Software Development
Computer Science
Electrical Engineering
Physical Science and Engineering
Artificial Neural Networks
Automation
Computer Vision
Control Systems
Convolutional Neural Networks
Deep Learning

Course Info

PlatformCoursera
LevelUnknown
PacingUnknown
PriceFree

Skills

تطوير البرمجيات
علوم الحاسوب
الهندسة الكهربائية
العلوم الفيزيائية والهندسة
الشبكات العصبية الاصطناعية
الأتمتة
رؤية الحاسوب
أنظمة التحكم
Convolutional Neural Networks
Deep Learning

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