Taking an online sensor fusion course is an easy way to get into machine learning. And it’s not just for people who want to make money from their skills. It can be a great way to learn about sensors, data collection and analysis, and how all the pieces fit together.
With that said, let’s dive right into the three best sensor fusion training courses online today.
3 Best Sensor Fusion Training Courses Right now
- Udemy’s ‘Become a Sensor Fusion Engineer’
Sometimes called one of the best options out there for learning sensor fusion outside a classroom setting, this Nanodegree certification from Udemy gives you a big boost in getting started with sensor fusion. The course itself is taught by a wide variety of qualified, experienced professionals who have been working in the field for a long time, and even features modern AI developers from leading companies like Ford (the automobile company) and Qualcomm (one of the world’s most famous manufacturers of mobile CPU chipsets).
It focuses on four mini courses that constitute the majority of the syllabus content, namely:
- Radar: This course is focused on using radar feedback from sensors to detect and track physical objects in an area. It teaches you how to handle actual data from a radar installation.
- Lidar: This introduces you to Lidar point clouds, which in turn helps you learn about things like obstacle clustering and Point Cloud Segmentation.
- Cameras: The third course focuses on sensor fusion in auto driving, and how to use camera images and lidar PCDs together.
- Kalman” The fourth and last course is about Kalman filters, and teaches you to make your own Kalman filter using C++, along with other things.
- Chalmers University of Technology’s ‘Sensor Fusion and Non-Liner Filtering for Automotive Systems
A Sensor Fusion Training Pune course that extensively uses MATLAB systems for learning, the Sensor Fusion and Non-Liner Filtering for Automotive Systems is a very industry-focused course from a leading Swedish University. You get to learn about course topics like:
- Motion models that are used for positioning
- The properties and usage of Kalman Filters
- Non-linear filtering
- Bayesian Statistics and Recursive Estimation Theory, and more.
A distinct advantage of this course is that it is very spaced out, and allows students to take their time with learning course content and giving their exams. According to a review and recommendation by Chalmers, 10-20 hours per week is quite sufficient for learning this course, and students studying at that rate will complete the course in about 8 weeks.
- Udemy’s ‘Advanced Kalman Filtering and Sensor Fusion
Udemy’s popular Advanced Kalman Filtering and Sensor Fusion is taught by Steven Dumble, a famous GN&C engineer with more than a decade of experience in software development. This course, unlike the others, focuses extensively on Kalman filters alone, and as such is the best choice out there if you’re choosing to learn a sensor fusion training course.
Here’s a rundown of what Dumble teaches you over the duration of the course:
- Setting up C++ development
- An introduction to Sensor fusion, Data fusion, and most importantly, Kalman filters,
- Linear, extended, and unscented Kalman filters,
- How to deal with faulty feedback and sensor biases,
- And many other topics that focus on the usage of Kalman filters.
Sensor fusion is an important technology, and it will only become even more so as autonomous cars, commercial drones, etc., become more common. Right now, signing up to learn a Sensor Fusion Course In Delhi course can set you up to reap the benefits from a field that’s just blooming!