Self-Driving Cars Specialization

Self-Driving Cars Specialization

Self-Driving Cars Specialization Launch Your Career in Self-Driving Cars. Be at the forefront of the autonomous driving industry. Taught in English 22 languages available Some content may not be translated Instructors: Steven Waslander +1 more Close Instructors Steven Waslander University of Toronto 4 Courses • 159,846 learners Jonathan Kelly University of Toronto 4 Courses •

Description

Self-driving cars have been gaining significant momentum in recent years as companies and researchers work to perfect the technology behind these innovative vehicles. One key aspect of self-driving cars that is often overlooked is the concept of specialization within the industry.

Specialization in the realm of self-driving cars refers to the development and implementation of specific technologies or capabilities that cater to different environments, use cases, or user needs. This approach recognizes that not all self-driving cars are created equal and that different situations may require different functionalities or features.

One common area of specialization within self-driving cars is the development of vehicles designed specifically for urban environments. These vehicles are optimized to navigate through congested city streets, deal with unpredictable traffic patterns, and interact with pedestrians and cyclists. Specialized sensors and algorithms are used to ensure smooth and safe operation in

Self-Driving Cars Specialization

Launch Your Career in Self-Driving Cars. Be at the forefront of the autonomous driving industry.

Taught in English

Some content may not be translated

Steven Waslander
Jonathan Kelly

Instructors: Steven Waslander

72,088 already enrolled

Included with Coursera Plus

Specialization – 4 course series

Get in-depth knowledge of a subject

4.7

(2,618 reviews)

Advanced level
Designed for those already in the industry
3 months at 10 hours a week
Flexible schedule
Learn at your own pace

What you’ll learn

  • Understand the detailed architecture and components of a self-driving car software stack

  • Implement methods for static and dynamic object detection, localization and mapping, behaviour and maneuver planning, and vehicle control

  • Use realistic vehicle physics, complete sensor suite: camera, LIDAR, GPS/INS, wheel odometry, depth map, semantic segmentation, object bounding boxes

  • Demonstrate skills in CARLA and build programs with Python

Details to know

Shareable certificate

Add to your LinkedIn profile

,

See how employees at top companies are mastering in-demand skills

About the author

Study on Scholarship Today -- Check your eligibility for up to 100% scholarship.