Key takeaways
- Self-driving technology has gained significant attention and development over the past decade, led by companies like Waymo and Tesla.
- The rise of autonomous vehicles has created new job opportunities in various fields, including engineering and software development.
- A wealth of online resources is available for individuals interested in learning about self-driving vehicles and related technologies.
- Courses such as 'The Complete Self-Driving Car Course' offer practical insights into computer vision and deep learning applications in automotive contexts.
Autonomous driving has been one of the holy grails in technology in the last decade. Waymo, Tesla, Faraday Future etc. have made huge inroads into self-driving tech and have been riding the AI wave to take us into the future. The mobility revolution has created new jobs, such as Industrial Engineer, Perception Software Engineers, Field Service Technicians, etc., to keep up with the demand. A lot of literature on autonomous driving is available on the internet as driverless cars continue to capture the public imagination.
Here, we have curated a list of the top 8 online resources for getting started with self-driving vehicles in 2021.
(The list is in no particular order)
1| The Complete Self-Driving Car Course - Applied Deep Learning
About: “The Complete Self-Driving Car Course - Applied Deep Learning”, offered by Udemy, will walk you through the fundamentals of Computer Vision and Deep Learning to help build automotive-related algorithms. You will also learn to build and train robust neural networks with Keras, train machine learning and deep learning models that can identify between 43 different Traffic Signs, understand, build and train Convolutional Neural Networks with Keras, etc.
Know more here.
2| Intro to Self-Driving Cars- Nanodegree Program
About: The nanodegree program offered by Udacity teaches you to work on autonomous car problems using languages like C++ and Python, computer vision/machine learning, etc. The course focuses on two tools that are vital to automobile engineers: object-oriented programming and linear algebra. You will also learn how a computer sees an image and how you can use machine learning to coach a computer to identify images programmatically.
Know more here.
3| Multi-Object Tracking for Automotive Systems
About: This course will take you through the fundamentals of multi-object tracking for automotive systems. This course's key components include the description and understanding of common sensors and motion models, principles underlying filters that can handle a varying number of objects, and a selection of the main multi-object tracking (MOT) filters.
Know more here.
4| Decision-Making for Autonomous Systems
About: This course will teach the fundamental mathematical model for real-world problems. You will learn how to use the Markov decision process ( a mathematical framework for modelling decision-making), understand and apply reinforcement learning and event-based methods, model and solve decision-making problems for autonomous systems, etc.
Know more here.
5| Autonomous Vehicles: A Complete Guide on Driverless Cars
About: The course gives you a 360-degree view of different aspects of autonomous vehicles. You will learn how autonomous or driverless vehicles are different from normal vehicles, various types of autonomous vehicles, technology architecture of driverless cars, different levels of autonomy and how they are decided, key hardware and software components of a driverless car, driver assistance systems and data processing elements etc.
Know more here.
6| Self-Driving Cars Specialization
About: The course gives you a comprehensive understanding of state-of-the-art engineering practices used in the self-driving car industry. You will get to interact with real-data sets from an autonomous vehicle (AV, all through hands-on projects using the open-source simulator CARLA) and learn from a highly realistic driving environment that features 3D pedestrian modelling and environmental conditions.
Know more here.
7| Autonomous Cars: Deep Learning and Computer Vision in Python
About: The course provides practical experience in various self-driving vehicles concepts such as machine learning and computer vision. The syllabus sheds light on concepts such as lane detection, traffic sign classification, vehicle/object detection, artificial intelligence, and deep learning. The topics and algorithms covered in this course include OpenCV, HOG feature extraction, Linear regression and logistic regression.
Know more here.
8| Self-Driving Cars Teach-Out
About: This course will address various topics on self-driving cars, such as what is an automated or driverless vehicle, how to test this technology and when can we expect to see it on the roads, how people are thinking about accessibility and equity, and the major legal questions etc.
Know more here.
