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所在平台: Coursera专项课程 课程类别: 计算机科学 大学或机构: CourseraNew |
课程主页: https://www.coursera.org/specializations/self-driving-cars
课程评论：没有评论
课程名称：无人驾驶汽车专业化 课程概述：本专业专注于自动驾驶行业的前沿技术。市场研究人士预测，到2025年，该行业市场将达到420亿美元，预计将有超过2000万辆无人驾驶汽车在路上。因此，未来将出现大量就业机会。 本专业提供对自动驾驶汽车（AV）行业最新工程实践的全面理解。学员将通过开源模拟器CARLA进行动手项目，使用真实的无人驾驶汽车数据集进行互动。 在课程中，行业专家将分享他们在Oxbotica和Zoox等公司的经验，讨论自动驾驶技术及其对就业增长的影响。学员将会在高度逼真的驾驶环境中学习，包括3D行人建模和各种环境条件。成功完成该专业后，学员将能够构建自己的自动驾驶软件堆栈，并为进入无人驾驶汽车行业做好准备。 建议学员具备线性代数、概率、统计、微积分、物理、控制理论及Python编程的背景知识。有效运行CARLA模拟器所需的系统要求包括：Windows 7 64位（或更高）或Ubuntu 16.04（或更高），四核Intel或AMD处理器（2.5 GHz或更快），NVIDIA GeForce 470 GTX或AMD Radeon 6870 HD系列显卡或更高，8 GB内存，以及OpenGL 3或更高版本（针对Linux计算机）。 课程大纲： 1. 自动驾驶汽车导论 - 描述：由多伦多大学提供的课程，欢迎参加自动驾驶汽车的导论课程。 - [查看课程链接](https://www.coursera.org/learn/intro-self-driving-cars) 2. 自动驾驶汽车状态估计与定位 - 描述：由多伦多大学提供的第二门课程，教授状态估计与定位。 - [查看课程链接](https://www.coursera.org/learn/state-estimation-localization-self-driving-cars) 3. 自动驾驶汽车视觉感知 - 描述：由多伦多大学提供的第三门课程，讲授视觉感知技术。 - [查看课程链接](https://www.coursera.org/learn/visual-perception-self-driving-cars) 4. 自动驾驶汽车运动规划 - 描述：由多伦多大学提供的第四门课程，聚焦运动规划技术。 - [查看课程链接](https://www.coursera.org/learn/motion-planning-self-driving-cars) 通过这些课程，您将具备在无人驾驶汽车行业工作的必要知识和技能。
Course Link: https://www.coursera.org/learn/intro-self-driving-cars
Name:Introduction to Self-Driving Cars
Description:Offered by University of Toronto. Welcome to Introduction to Self-Driving Cars, the first course in University of Toronto’s Self-Driving ... Enroll for free.
Course Link: https://www.coursera.org/learn/state-estimation-localization-self-driving-cars
Name:State Estimation and Localization for Self-Driving Cars
Description:Offered by University of Toronto. Welcome to State Estimation and Localization for Self-Driving Cars, the second course in University of ... Enroll for free.
Course Link: https://www.coursera.org/learn/visual-perception-self-driving-cars
Name:Visual Perception for Self-Driving Cars
Description:Offered by University of Toronto. Welcome to Visual Perception for Self-Driving Cars, the third course in University of Toronto’s ... Enroll for free.
Course Link: https://www.coursera.org/learn/motion-planning-self-driving-cars
Name:Motion Planning for Self-Driving Cars
Description:Offered by University of Toronto. Welcome to Motion Planning for Self-Driving Cars, the fourth course in University of Toronto’s ... Enroll for free.
Be at the forefront of the autonomous driving industry. With market researchers predicting a $42-billion market and more than 20 million self-driving cars on the road by 2025, the next big job boom is right around the corner. This Specialization gives you a comprehensive understanding of state-of-the-art engineering practices used in the self-driving car industry. You'll get to interact with real data sets from an autonomous vehicle (AV)―all through hands-on projects using the open source simulator CARLA. Throughout your courses, you’ll hear from industry experts who work at companies like Oxbotica and Zoox as they share insights about autonomous technology and how that is powering job growth within the field. You’ll learn from a highly realistic driving environment that features 3D pedestrian modelling and environmental conditions. When you complete the Specialization successfully, you’ll be able to build your own self-driving software stack and be ready to apply for jobs in the autonomous vehicle industry. It is recommended that you have some background in linear algebra, probability, statistics, calculus, physics, control theory, and Python programming. You will need these specifications in order to effectively run the CARLA simulator: Windows 7 64-bit (or later) or Ubuntu 16.04 (or later), Quad-core Intel or AMD processor (2.5 GHz or faster), NVIDIA GeForce 470 GTX or AMD Radeon 6870 HD series card or higher, 8 GB RAM, and OpenGL 3 or greater (for Linux computers).
无人驾驶汽车专业化：处于自动驾驶行业的最前沿。市场研究人员预测，到2025年，这一市场的规模将达到420亿美元，无人驾驶汽车将超过2000万辆，下一个巨大的就业热潮即将来临。 通过本专业知识，您可以全面了解自动驾驶汽车行业中使用的最新工程实践。您将通过使用开源模拟器CARLA的动手项目，与自动驾驶汽车（AV）的真实数据集进行交互。 在整个课程中，您会听到在Oxbotica和Zoox等公司工作的行业专家的见解，他们分享了有关自动驾驶技术及其如何推动该领域工作增长的见解。 您将从具有3D行人建模和环境条件的高度逼真的驾驶环境中学习。成功完成专业化培训后，您将能够构建自己的自动驾驶软件堆栈，并准备申请自动驾驶汽车行业的工作。 建议您具有线性代数，概率，统计，微积分，物理，控制理论和Python编程的背景知识。您需要以下规范才能有效运行CARLA模拟器：Windows 7 64位（或更高版本）或Ubuntu 16.04（或更高版本），四核Intel或AMD处理器（2.5 GHz或更快），NVIDIA GeForce 470 GTX或AMD Radeon 6870 HD系列卡或更高版本，8 GB RAM和OpenGL 3或更高版本（对于Linux计算机）。
