Self-Driving Car Specialization Course
About this course
Updated in May 2025. This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Embark on a transformative journey into the cutting-edge world of self-driving cars with this comprehensive specialization. Learn the core concepts, technologies, and systems that make autonomous vehicles a reality. From foundational principles to advanced decision-making, this course equips you with the expertise needed to design, implement, and test self-driving car technologies. The course begins with an introduction to autonomous vehicles, exploring their history, levels of automation, and the essential hardware and software components. Progress to system design and control systems, where you’ll master key topics like PID controllers, feedforward and feedback control, Kalman filters, and time-to-collision calculations. Delve into computer vision techniques, including object detection, semantic segmentation, and depth perception, critical for safe and accurate navigation. Engage in hands-on simulations with ROS and Gazebo, developing models, mapping environments, and implementing motion prediction. Finally, experiment with Jetbot implementation, integrating cutting-edge technologies like the Jetson Nano for real-world testing and optimization. This course is perfect for aspiring engineers, researchers, and professionals in autonomous driving. A background in programming, robotics, or vehicle dynamics is helpful but not mandatory. Suitable for intermediate learners eager to dive into the autonomous vehicle revolution.
81/100
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- 20/35
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- 16/20
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What you'll learn
- understand the history and levels of automation in autonomous vehicles
- implement control systems using PID controllers and Kalman filters
- apply computer vision techniques like object detection and semantic segmentation
- develop models and simulations using ROS and Gazebo
- integrate Jetbot implementations for practical testing
Course objectives
- equip students with the skills to design self-driving car technologies
- enhance understanding of the systems and technologies in autonomous driving
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