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所在平台: Udemy |
课程主页: https://www.udemy.com/course/introduction-to-ai-for-landscape-architects-and-designers/
课程评论：没有评论
课程名称：景观建筑师的生成性人工智能概论 课程概述： 本课程是针对信息技术（IT）和人工智能（AI）领域的入门课程，专为没有IT或AI背景的学生设计，无需编程技能。课程旨在简明扼要地传授从学术出版物和博士论文中获得的经验，尝试将景观建筑和人工智能这两个主题结合起来。该课程适合希望开发新方法和新思路的建筑、城市规划和景观建筑学生，是对人工智能的简短介绍，旨在满足来自教育机构和职业培训机构的反馈需求，提供简单易懂的基础培训。 课程内容包括： - 历史发展 - 基本概念 - 生成模型与建筑环境的关系 - 机器学习 - 人工神经网络 - 生成模型 - CAD、BIM、GIS和AI - 大语言模型 - 提示工程 - Autodesk Forma应用 - 道德伦理 - 结论 - 额外内容 本课程通过清晰有序的方式解释被认为复杂的人工智能主题，使得对建筑环境设计感兴趣的学科，以及艺术家和其他爱好者都方便理解。课程内容汇集了在六年集中的学习过程中从多个Udemy在线课程和大学获得的知识与经验。
An introductory course on IT and Artificial Intelligence (AI) was presented, covering the topics listed below. This course aims to teach AI and its related concepts to students with no prior knowledge of IT or AI, without requiring any coding skills. It is aimed to clearly convey the experience gained through academic publications and all the details of the doctoral thesis that try to bring together the subjects of landscape architecture and artificial intelligence. It is planned to be a short introduction to artificial intelligence for architecture, urban planning and landscape architecture students who want to develop new methods and approaches. This content was created with the feedback received from educational institutions and professional vocational institutions that requested this simple introduction training. A curriculum that explains the subject of AI, which is considered complex and difficult to learn, in a simple and organized way was created. In addition to explaining it to disciplines interested in built environment design, it was also intended to be explained in a structure that artists and other enthusiasts can understand. It is an introduction to the field of IT, where the knowledge and experience learned from dozens of online courses of Udemy and universities during the six-year intensive education process is briefly transferred.Topics covered:Historical DevelopmentBasic ConceptsGenerative Models and Built Environment RelationshipMachine LearningArtificial Neural NetworksGenerative ModelsCAD, BIM, GIS, and AILarge Language ModelsPrompt EngineeringAutodesk Forma ApplicationEthicsConclusionsAdditionals
