AICurious’s learning notes for this course: https://aicurious.io/posts/apollo-sdc-lessons-intro/
This is an introduction course to self-driving cars and Apollo platform. Through this course, you will be able to identify key parts of self-driving cars and get to know Apollo architecture. You will be able to utilize Apollo HD Map, localization, perception, prediction, planning and control, and start the learning path of building a self-driving car.
Following Udacity, in this course, you’ll sharpen your Python skills, apply C++, apply matrices and calculus in code, and touch on computer vision and machine learning. These concepts will be applied to solving self-driving car problems. This course is a preparation for Udacity Self-Driving Car Nanodegree below.
You’ll first apply computer vision and deep learning to automotive problems, including detecting lane lines, predicting steering angles, and more. Next, you’ll learn sensor fusion, which you’ll use to filter data from an array of sensors in order to perceive the environment. Finally, you’ll have an opportunity to run your code in a simulation on Udacity’s self-driving car. - Udacity.
This class is an introduction to the practice of deep learning through the applied theme of building a self-driving car. It is open to beginners and is designed for those who are new to machine learning, but it can also benefit advanced researchers in the field looking for a practical overview of deep learning methods and their application.
This course brings together all the significant parts into a practical step-by-step guide to architect, develop, test, and deploy an autonomous system using the popular open-source robotics frameworks ROS 2 and Autoware.Auto.
This course was produced by Toronto University on Coursera platform. It 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. - Coursera.