Izvēlne Aizvērt

Autonomie auto

Self-Driving Cars Specialization

Šis kurss ļaus jums iepazīt nozari, kuras attīstība nozīmēs izmaiņas mūsu ikdienas transporta paradumos un veidos jaunu autonomā transporta industriju. Kursa ietvaros jums būs iespēja saprast, kā top mūsdienīgi tehniskie risinājumi paš-braucošo transporta līdzekļu attīstībai un dzirdēt ekspertus, kas iepazīstinās ar nākotni, kura top jau šodien.

€73/mēnesī

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Advanced Level

Iepriekšēja pieredze nav nepieciešama.

7 mēneši

Kursa apgūšanai nepieciešami 7 mēneši – 5 stundas nedēļā

Valoda

angļu valodā
subtitri – angļu un spāņu valodā.

Kursa mācību plāns

1. KURSS

Introduction to Self-Driving Cars

35 H

2. KURSS

State Estimation and Localization for Self-Driving Cars

27 H

3. KURSS

Visual Perception for Self-Driving Cars

31 H

4. KURSS

Motion Planning for Self-Driving Cars

32 H

  • Understand the detailed architecture and components of a self-driving car software stack
  • Use realistic vehicle physics, complete sensor suite: camera, LIDAR, GPS/INS, wheel odometry, depth map, semantic segmentation, object bounding boxes
  • Implement methods for static and dynamic object detection, localization and mapping, behaviour and maneuver planning, and vehicle control
  • Demonstrate skills in CARLA and build programs with Python

Pabeidzot katru kursu un izpildot praktisko projektu, jūs iegūstat sertifikātu. Sertifikāts ir printējams, kā arī jūs varat dalīties ar saviem kursu sertifikātiem sava LinkedIn profila sadaļā Sertifikācijas. “Shareable on Linkedin”

  • University of Toronto

Steven Waslander

Associate Professor

Jonathan Kelly

Assistant Professor

Coursera - FAQ

If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time.

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the “Enroll” button on the left. You’ll be prompted to complete an application and will be notified if you are approved. You’ll need to complete this step for each course in the Specialization, including the Capstone Project.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

This Specialization doesn’t carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

Each course is intended to take 4-6 weeks, roughly one week per module. At this pace, the entire Specialization will take you 4-6 months to complete.

See the list of prerequisites provided in Module 0 of Course 1. The most important ones are familiarity with linear algebra, calculus, probability theory, and kinematic and dynamic modeling. Some exposure to computer vision, AI or robotics is also useful.

The courses are mostly independent and self-paced, so it is possible to mix the order of the courses based on your interests. The only exception is that Course 1 provides a valuable overview of an autonomous vehicle in terms of hardware and software, so we recommend starting with Course 1.

You will be able to develop basic implementations of all the main components of an autonomous car software stack, including localization and mapping solutions, object detection and drivable surface detection methods, motion planning approaches and vehicle controllers. You’ll be ready to enter the industry with a strong overview of the core requirements and challenges in self-driving development, and you’ll have experience with simulating these vehicles in the CARLA simulator.

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