Autonomous Robots: Kalman Filter
Original price was: $109.99.$18.99Current price is: $18.99.
What you’ll learn
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Proficiency with Kalman Filters.
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General understanding of the whole robotic software stack.
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Solve real world problems that self-driving cars or autonomous cars face.
Autonomous Robots Are The Future. Learn to Program Them With My Fast, Easy to Understand Course!
For lovers of cars, technology and robotics alike, my online course can teach you how to write the software needed to make a self-driving car work.
Regardless of your experience in coding, by the end of this course you will not only be proficient with Kalman Filters, but you’ll have an understanding of how robotics software works and how to write code in Python.
My goal with every course I make is to meet you where you’re at. You can be completely new to robotics, never having coded a thing in your life, and in only two hours you’ll have the knowledge needed to write a code that is ready to be tested in my custom simulator.
If you are already a coding expert, this in-depth look at how Kalman Filters function will help you diversify your robotics arsenal and level up your confidence in working with autonomous robots.
But this course isn’t just about accumulating knowledge. What sets this apart from other online robotics programs is that I make the process fun. You get to see what the real-life results of your code would look like with a simulated self-driving car. Robotics can (and should) be a field full of exploration, experimentation, fun, and getting your hands dirty. With my courses, I make that a priority, even in an online setting.
Want to see for yourself?
Check out the course to see how you can level up your skills today.
Who this course is for:
- Anyone who is interested in robotics, self-driving cars, or autonomous vehicles in general.
12 reviews for Autonomous Robots: Kalman Filter
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Original price was: $109.99.$18.99Current price is: $18.99.
András Jánosi –
The course gives a very good introduction to Kalman filters, by leaving out the theory of it but rather learn it by experience. I would appreciate sometimes a little-bit more explanation though.
I was starting from a basic knowledge of Kalman filters (main areas of usage) at the beginning of the course, but after it I think I will be able to use it in real life implementations.
Igor Erceg –
Good intro to Kalman filter. I like the way Mr. Stang explains the usage of the Kalman filter. I’d like a little bit more theory regarding design and choosing the values for the matrices. I know this is not a mathematical modeling course, but it wouldn’t hurt to give some car modeling materials (e.g., web pages, additional text materials, etc.). This would be of great help in better understanding how the system works.
Sherin Abraham –
My questions were not answered on time. Concepts could have been explained better.
Jacob Varughese –
The course was informative and armed me with a basic understanding of what a Kalman filter is. It has certainly cleared the grey cloud obstructing my understanding of what a Kalman filter is. I would prefer if this was also implemented on Simulink for the ease of visualization.
Peng Xu –
The content is designed very concise and effective
Fabian Scheidt –
Nice course.
Lynnette M Patton –
good detailed description of concepts, i think a little animation here would go a long ways. I already want to put together a spreadsheet with the filter matrices denote the inputs with conditional formatting instructions to make things a little more interactive and visual. I haven’t gone full Python yet
Shing Yan Loo –
I had some background knowledge about Kalman filter. I was hoping to get some additional practice through the exercises. While the answers make sense, the exercises themselves lack documentation, e.g., a short description at the top of each exercise would be nice so we won’t need to revisit the videos just to catch the minor details. Also, it would be great to explain the state and measurement transition functions (the Jacobians) and how are they related to the state and the measurements.
Muhammad Saad Tahir –
Not what I expected. It feels like rather than teaching Kalman Filters, the instructor is just showing his work assuming we know are understanding everything! Definitely not recommended for beginners!
Manuel Espino –
Quite short
Phuc Thien NGUYEN –
Great experiences to start with Kalman filter with hands-on assigment.
Siddharth Atul Joshi –
Too short, nothing mentioned in detailed. Simulator is not good. I did not like at all.