autonomous driving online course

Last Updated on August 8, 2022 by Team College Learners

This autonomous vehicles course introduces you to the revolutionary field of autonomous driving. From the basic theory behind self-driving cars, through cutting edge deep learning applications, to demonstrations in real-world scenarios—you’ll learn just how close we are to having cars drive us, rather than the other way around.

Online course as you may have read on the news with autonomous cars becoming a reality. Come join the movement and explore in depth about the intuition and future of Autonomous Driving. We pride ourselves in teaching most up to date curriculum available in university’s and companies alike. Furthermore, you will have access to exclusive insight from the leading names in Autonomous vehicles. The autonomous vehicles course is open for people of all ages and backgrounds, no prerequisites are required. We care about building a community of like-minded individuals so we offer a continuous support via our instructor/student forum. You will also receive your certificate upon completion. Enjoy!

best self-driving car course

Road to 2030: the Future of Autonomous Vehicles (AVs)

1. The Complete Self-Driving Car Course – Applied Deep Learning (Udemy)

Learn to use Deep Learning, Computer Vision and Machine Learning techniques to Build an Autonomous Car with Python.Tip: Get a discount on Udemy courses when you sign up through Learn Robotics.

2. Intro to Self-Driving Cars Nanodegree (Udacity)

Udacity also offers a four-month Nanodegree called the “Intro to Self-Driving Cars.” In this program, you’ll earn the essentials of building a self-driving car, including probability, C++, machine learning, and linear algebra.

The Intro to Self-Driving Cars Nanodegree is designed to prepare you for the advanced Self-Driving Car Engineer Nanodegree, which we’ll talk about next.

3. Self-Driving Car Engineer Nanodegree (Udacity)

The Intro Nanodegree is designed for beginner to intermediate software developers looking to get into autonomous vehicles. The Self-Driving Car Engineer Nanodegree is for people who are more advanced in their careers.

In this course, you’ll focus on computer vision topics including how to find lane lines on the road and advanced lane finding algorithms.

The content was co-created with Mercedes-Benz, so if you’re looking to break into a large automotive company, having this nanodegree on your resume, could be beneficial.

At the end of this course, you’ll know a breadth of self-driving car engineering topics: sensor fusion, localization, planning, control, system integration.

4. State Estimation & Localization for Self-Driving Cars (Coursera)

Another self-driving car course with great reviews (4.7 stars) is offered by the University of Toronto on Coursera. (They also have a Self-Driving Car Specialization, and this happens to be one of the courses in the series.)

The State Estimation and Localization course is designed for advanced-level learners and can be completed in about a month.

“One of the most exciting courses ever had in terms of learning and understanding. Kalman filter is a fascinating concept with infinite applications in real life on daily basis.” -AQ, Student February 2020

Expect to spend about 15 hours a week on this course, and get ready to build a bunch of self-driving car algorithms and software projects.

Autonomous Vehicle Online Courses

Additionally, there are more courses you can take with an emphasis on autonomous vehicle systems. In these courses, you’ll learn key principles in autonomous decision-making, sensor fusion, and multi-object tracking for automotive systems.

1. Self-Driving Car Specialization (Coursera)

As I mentioned above, you can enroll in the Self-Driving Car specialization on Coursera. The entire specialization takes about five months to complete and costs $79 per month.

There are four courses in this specialization:

  1. Intro to Self-Driving Cars;
  2. State Estimation and Localization;
  3. Visual Perception for Self-Driving Cars; and,
  4. Motion Planning for Self-Driving Cars.

Tip: If you plan on spending five months in this specialization, your best bet is to enroll in Coursera Plus. For $4 more than the specialization, you’ll gain one-year access to over 3,000+ courses and specializations. It’s a great deal and will save you money if you don’t finish the specialization within five months.

2. Multi-Object Tracking for Automotive Systems (edX)

The Multi-Object Tracking (MOT) for Automotive Systems course is taught by the Chalmers University of Technology on edX.

In this self-driving car course, you’ll learn how to localize and track dynamic objects with a range of applications including autonomous vehicles.

By the end of this course, you’ll have a thorough understanding of:

  • multi-object tracking;
  • an expert-level understanding of principles, theories, and algorithms using modern multi-object tracking;
  • extensive problem-solving skills for putting MOT in practice; and,
  • experience you can showcase on your resume or job application.

3. Sensor Fusion & Non-linear Filtering for Automotive Systems (edX)

Additionally, at the Chalmers University of Technology, you can take a course on Sensor Fusion and Non-linear Filtering for Automotive Systems.

This course will teach you the fundamental algorithms for sensor fusion and non-linear filtering with application to automotive perception systems.

Sensor fusion is an integral part of self-driving cars, so there are many options taught by multiple universities and online platforms. If you find that you are having trouble learning this material from one instructor, try learning the material on a different platform.

4. Decision-Making for Autonomous Systems (edX)

Lastly, edX offers a course called, “Decision-Making for Autonomous Systems.”

This course is aimed at students with Bachelor degrees or engineers in the automotive industry who want to have more in-depth knowledge about decision-making models.

This course will teach you the fundamental mathematical models for many of these real-world problems.

Key topics of this self-driving car course include:

  • Markov decision process;
  • reinforcement learning and event-based methods; and,
  • modeling and solving of decision-making for autonomous systems.

Get ready to learn the mathematical models behind real-world automotive challenges, while figuring out the decision-making process for autonomous vehicles.

5. Sensor Fusion Engineer Nanodegree (Udacity)

Additionally, you can gain specialized knowledge in sensor fusion by taking the Sensor Fusion Engineer Nanodegree program on Udacity.

Learn to fuse lidar point clouds, radar signatures, and camera images using Kalman Filters to perceive the environment and detect and track vehicles and pedestrians over time.Click here to learn more about the Sensor Fusion Engineer Nanodegree program on Udacity.