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Self-driving, or autonomous, cars do not exist yet and they likely won’t for many years. But the University of Toronto (U of T) wants to help create and launch the driverless future that many major automotive manufacturers are focused on right now. U of T teamed with online learning tool Coursera to offer a Self-Driving Cars Specialization that includes four web-based software development courses. All four courses are currently open for enrollment.
Launched at the beginning of 2019, the U of T computer science specialization breaks down into four parts. Course one, “Introduction to Self-Driving Cars,” teaches the basic terminology, design considerations, and safety assessment of self-driving cars. Course two, “State Estimation and Localization,” explains the various sensors in self-driving cars and how they are used for determining the vehicle’s operating state and location.
The third course, “Visual Perception for Self-Driving Cars,” will guide students through the “main perception tasks in autonomous driving, static and dynamic object detection,” and “common computer vision methods for robotic perception.” The fourth course, “Motion Planning for Self-Driving Cars,” discusses the “main planning tasks in autonomous driving, including mission planning, behavior planning, and local planning.”
Coursera says all four courses could be completed in four to six months using the recommended schedule of six hours per week. The courses are taught by Associate Professors Steven Waslander and Jonathan Kelly, both of whom specialize in aerospace studies.
In addition to insight from experts from companies Oxbotica and Zoox, the specialization also includes work with open-source simulator CARLA. A hands-on project is required to complete the specialization and earn a certificate. To be clear, earning a certificate requires payment, but the courses can be viewed using the audit option. The course otherwise comes as part of Coursera Plus, which is $79 per month.
There is a bit of catch to all of this. Coursera suggests specific tech equipment and recommends students have some prior experience with the tools that will be used throughout the courses:
“It is recommended that you have some background in linear algebra, probability, statistics, calculus, physics, control theory, and Python programming,” the description says. “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).”
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