Autonomous Cars: Deep Learning and Computer Vision in Python
The automobile industry is transitioning from traditional, human-driven cars to self-driving, artificial intelligence-powered vehicles. Self-driving cars provide a safe, efficient, and cost-effective option that will fundamentally alter the future of human mobility. Self-driving cars are predicted to save over 500,000 lives and provide tremendous economic potential worth more than $1 trillion by 2035. The automobile industry is investing billions of dollars in order to put the most technologically sophisticated vehicles on the road. As the globe moves closer to a driverless future, the demand for competent engineers and researchers in this growing new industry has never been greater. The goal of this course is to teach students about the major components of self-driving car design and development.
The course gives students hands-on experience with self-driving car topics, including machine learning and computer vision. Lane detection, traffic sign categorization, vehicle/object detection, artificial intelligence, and deep learning are among the concepts covered. The course is designed for students who wish to learn the fundamentals of self-driving car control. A basic understanding of programming is recommended. However, because these subjects will be thoroughly addressed throughout the first few course sessions, the course has no prerequisites and is available to any student with basic programming skills. Students who take this self-driving vehicle course will learn about driverless automobile technology that will change the world.
Who this course is for:
- Software engineers interested in learning the algorithms that power self-driving cars.
Requirements:
- Windows, Mac, or Linux PC with at least 3GB free disk space.
- Some prior experience in programming.
Udemy rating: 4.6/5
Enroll here: https://www.udemy.com/course/autonomous-cars-deep-learning-and-computer-vision-in-python/
