[University of Toronto] Self-Driving Cars Specialization

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).

Course Duration

Approx. 2 months to complete
Suggested 12 hours/week, online, flexible schedule
If you cannot afford the course fee, you can apply for financial aid.

Self-Driving Cars. Become an autonomous vehicle engineer.

Course Content

There are 4 courses in this Specialization:

Course 1: Introduction to Self-Driving Cars

Course 2: State Estimation and Localization for Self-Driving Cars

Course 3: Visual Perception for Self-Driving Cars

Course 4: Motion Planning for Self-Driving Cars

Course Outcome

You will be able to develop basic implementations of all the main components of an autonomous car software stack, including localization and mapping solutions, object detection and drivable surface detection methods, motion planning approaches and vehicle controllers. You’ll be ready to enter the industry with a strong overview of the core requirements and challenges in self-driving development, and you’ll have experience with simulating these vehicles in the CARLA simulator.

[University of Toronto] Self-Driving Cars Specialization


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