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Learner Reviews & Feedback for State Estimation and Localization for Self-Driving Cars by University of Toronto

641 ratings
106 reviews

About the Course

Welcome to State Estimation and Localization for Self-Driving Cars, the second course in University of Toronto’s Self-Driving Cars Specialization. We recommend you take the first course in the Specialization prior to taking this course. This course will introduce you to the different sensors and how we can use them for state estimation and localization in a self-driving car. By the end of this course, you will be able to: - Understand the key methods for parameter and state estimation used for autonomous driving, such as the method of least-squares - Develop a model for typical vehicle localization sensors, including GPS and IMUs - Apply extended and unscented Kalman Filters to a vehicle state estimation problem - Understand LIDAR scan matching and the Iterative Closest Point algorithm - Apply these tools to fuse multiple sensor streams into a single state estimate for a self-driving car For the final project in this course, you will implement the Error-State Extended Kalman Filter (ES-EKF) to localize a vehicle using data from the CARLA simulator. This is an advanced course, intended for learners with a background in mechanical engineering, computer and electrical engineering, or robotics. To succeed in this course, you should have programming experience in Python 3.0, familiarity with Linear Algebra (matrices, vectors, matrix multiplication, rank, Eigenvalues and vectors and inverses), Statistics (Gaussian probability distributions), Calculus and Physics (forces, moments, inertia, Newton's Laws)....

Top reviews

Oct 13, 2019

There are many interesting topics. Without the help and suggested readings from this course, I wouldn't be able to finish by myself. Also, the final project is very enlightening.

Feb 8, 2020

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.

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51 - 75 of 105 Reviews for State Estimation and Localization for Self-Driving Cars

By Karthik B K

Jun 29, 2019

Really Advanced and Challenging Course with great scope of gaining knowledge.

By Mehran R

Sep 15, 2020

It requires a bit of external studying, but in general, it's a great course.

By huseyin t

Feb 14, 2021

Perfect lecture. Nicely designed assignments and very nice reading advices.

By Levente K

Mar 1, 2019

Sometimes hard, but still pretty much fun to solve all the problems :)

By 78 F V R S

Oct 15, 2020

I had an amazing experience got to learn new things from this course

By Ahmed E

Apr 12, 2020

This course was very useful. It will significantly help in my career

By Stefan M

Aug 15, 2019

From my point of view a very interesting and well prepared course.

By Kosinski K

May 25, 2020

The great course! Very good presentations and nice projects.


Nov 13, 2020

Great Experience. I had learned some much from this course.


Mar 4, 2020

The last assignment for this module is very challenging.

By Akash B

Jun 16, 2020

Course was good, need more guidance for calculations.

By Guillermo P G

May 13, 2020

Amazing course, congratulations, I have learnt a lot!

By jinglong

May 27, 2020

very nice tutorials for autonomous driving beginner.


Oct 8, 2019

it's really nice, and amazing course. I enjoyed it

By Felipe M G

Oct 26, 2020

This is a excellent course with great proffesors

By Varun J

May 13, 2020

Indeed one of the best courses here at Coursera!

By Ansh S

Aug 14, 2020

Amazing specialisation to get aquainted to SLAM

By Jose C I G Z

Dec 9, 2020

Awesome course and very challenging!

By 刘宇轩

Apr 25, 2019

The projects are useful enough

By Shridhar N V

Jun 8, 2020

Kalman filter was interesting

By Vishwas N

Apr 29, 2020

very nicely crafted course

By Luis E T R

Sep 13, 2020

An outstanding course

By Sujeet B

Dec 7, 2020

Lot's of learning...


May 28, 2020

Many many thanks!


May 30, 2020

Very Infomative!