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Coursera offers the Estimation and Localization for Self-Driving Cars certification course in association with the University of Toronto. The certification course introduces students to different sensors for correctly estimating the state and localization of a self-driving vehicle.
Moreover, by the end of the Estimation and Localization for Self-Driving Cars course, you will learn all about Kalman Filters and Iterative Closest Point algorithm with LIDAR. The certification course will also cover least squares, and how to relate GPS with IMUs. You will be able to build models for typical vehicle localization sensors.
Upon course completion, you will become adept in developing a full vehicle state estimator independently. The course material is comprehensive and features quizzes, as well as projects, to assist you in learning with ease.
Lastly, candidates will undertake a final project to complete the Coursera State Estimation and Localization for Self-Driving Cars course. On successful completion, candidates will receive a certificate from the University of Toronto, sharable on LinkedIn profiles or CV.
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The State Estimation and Localization for Self-Driving Cars fees details:
To join the Coursera State Estimation and Localization for Self-Driving Cars course, candidates must have programming experience with Python 3.0. Additionally, you should have an advanced understanding of Physics, Calculus, Linear Algebra, and Statistics to derive maximum benefit from this certification programme.
State Estimation and Localization for Self-Driving Cars programme, will expose you to a host of critical information. After course completion, you should be able to perform the following:
The State Estimation and Localization Accreditation online course is primarily suitable for professionals from the engineering background. The certification course will prove beneficial for professionals such as:
You can register for the State Estimation and Localization for Self-Driving Cars online course using the following steps:
Step 1. Visit the course page.
Step 2. Click the ‘Enroll for Free’ button.
Step 3. Sign up Coursera using either your email ID or Google account.
Step 4. Finally, choose a course mode and pay the fee accordingly.
No separate application form is needed for the State Estimation and Localization for Self-Driving Cars programme. You can simply sign-up for free using your Apple, Google, or Facebook account. You can also sign-up with your email address and access the course content instantly.
The automobile industry is undergoing a silent revolution, as developers test out novel technology in the autonomous driving sector. Top market researchers predict exponential growth of this sector by the turn of this decade. Therefore, if you have the aptitude, you can sign-up and upskill to boost your career.
Applicants must have advanced knowledge of Physics, Calculus, Linear Algebra, and Statistics. Additionally, they must have programming experience with Python 3.0.
The training module is completely virtual, with flexible deadlines. Candidates take typically Approx 26 hours to complete the programme. While the lessons are in English, candidates receive subtitles in various languages. In the end, the learner will receive the course certificate, which is sharable on the LinkedIn profile.
Yes, you will receive a host of benefits, but the biggest is the e-Certificate of Specialization. The Certificate is sharable on your LinkedIn profile and will boost your credibility in the field. Additionally, you will have access to curated projects and quizzes.
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