市场正在惩罚只懂理论的端到端算法工程师......

Core Insights - The article discusses the current challenges in the automotive industry regarding the recruitment of algorithm talent for end-to-end production roles, highlighting a gap between the skills of candidates and the high salary expectations for these positions [1] - A new course titled "End-to-End Practical Class for Mass Production" has been designed to address this gap, focusing on essential algorithms and practical applications in autonomous driving [1] Course Overview - The course is structured into eight chapters, covering various aspects of end-to-end algorithms, including the integration of perception tasks and learning-based control algorithms [6] - It emphasizes the importance of understanding both one-stage and two-stage end-to-end frameworks, with practical examples and real-world applications [7][8] - Key algorithms discussed include reinforcement learning, trajectory optimization, and spatial-temporal planning, which are crucial for the mass production of autonomous driving systems [10][12] Target Audience - The course is aimed at advanced learners with a foundational understanding of autonomous driving technologies, including familiarity with algorithms such as reinforcement learning and diffusion models [14][16] - It is designed to be accessible even to those with weaker foundations, as the instructor will provide guidance to help participants quickly get up to speed [14] Course Logistics - The course will commence on November 30 and is expected to last for three months, featuring offline video lectures and online Q&A sessions [14][17] - Participants are required to have a GPU with a recommended capability of 4090 or higher, along with a basic understanding of Python and PyTorch [16]