Dr. Leo Porter is a Teaching Professor in the Computer Science and Engineering Department at UC San Diego. He is best known for his research on the effect of peer instruction in computing courses, the use of clicker data to predict student outcomes, and the development of the Basic Data Structures Concept Inventory. He co-teaches the popular Coursera Specialization “Object-Oriented Java Programming: Data Structures and Beyond” with more than 300,000 enrolled learners and the first course in the edX MicroMasters in Data Science, “Python for Data Science”, with more than 200,000 enrolled learners. He has received six Best Paper Awards, SIGCSE’s 50th Year Anniversary Top Ten Symposium Papers of All Time Award, an Outstanding Teaching Award from Warren College, and the Academic Senate Distinguished Teaching Award at UC San Diego. He is a Distinguished Member of the ACM and previously served on the ACM SIGCSE Board.
利奥·波特（Leo Porter）博士是加州大学圣地亚哥分校计算机科学与工程系的教学教授。他以研究计算机课程中“同伴指导”的效果、利用点答器数据预测学生成绩以及设计出基本数据结构的概念清单而闻名。他与人合教了广受好评的Coursera专项课程“面向对象的Java编程：数据结构及其超越”，有超过30万名学员注册学习；以及edX MicroMasters平台上数据科学专业的第一门课程“Python for Data Science”，有超过20万名学员注册学习。他曾获得六项最佳论文奖，SIGCSE 50周年纪念十大研讨会论文奖，沃伦学院杰出教学奖，以及加州大学圣地亚哥分校学术参议院杰出教学奖。他是ACM的杰出会员，并且曾在ACM SIGCSE董事会任职。
Dr. Daniel Zingaro is an Associate Teaching Professor at University of Toronto. He has taught introductory Python programming to thousands of students over the past 15 years and wrote the Python textbook that is currently being used for the course. He has also written dozens of research articles about how to teach and learn introductory CS. Dan has written two books with No Starch Press—the aforementioned one on Python and one on algorithms—that have been translated into multiple languages. Dan has received several prestigious teaching and research awards, including a 50-Year Test of Time award and multiple Best Paper awards.
Peter Morgan is the founder of the AI consulting company Deep Learning Partnership based in London (www.deeplp.com). He has an advanced degree in physics along with an MBA. He has been working in AI for the past ten years and before that spent ten years as a Solutions Architect for companies such as Cisco Systems and IBM. Peter has written several reports, papers and book chapters on AI, physics, and quantum computing. He consults on LLMOps and quantum computing for startups and enterprises globally. You can follow Peter on Twitter (@PMZepto).
About the Authors
关于作者
Dr. Leo Porter is a Teaching Professor in the Computer Science and Engineering Department at UC San Diego. He is best known for his research on the effect of peer instruction in computing courses, the use of clicker data to predict student outcomes, and the development of the Basic Data Structures Concept Inventory. He co-teaches the popular Coursera Specialization “Object-Oriented Java Programming: Data Structures and Beyond” with more than 300,000 enrolled learners and the first course in the edX MicroMasters in Data Science, “Python for Data Science”, with more than 200,000 enrolled learners. He has received six Best Paper Awards, SIGCSE’s 50th Year Anniversary Top Ten Symposium Papers of All Time Award, an Outstanding Teaching Award from Warren College, and the Academic Senate Distinguished Teaching Award at UC San Diego. He is a Distinguished Member of the ACM and previously served on the ACM SIGCSE Board.
利奥·波特（Leo Porter）博士是加州大学圣地亚哥分校计算机科学与工程系的教学教授。他以研究计算机课程中“同伴指导”的效果、利用点答器数据预测学生成绩以及设计出基本数据结构的概念清单而闻名。他与人合教了广受好评的Coursera专项课程“面向对象的Java编程：数据结构及其超越”，有超过30万名学员注册学习；以及edX MicroMasters平台上数据科学专业的第一门课程“Python for Data Science”，有超过20万名学员注册学习。他曾获得六项最佳论文奖，SIGCSE 50周年纪念十大研讨会论文奖，沃伦学院杰出教学奖，以及加州大学圣地亚哥分校学术参议院杰出教学奖。他是ACM的杰出会员，并且曾在ACM SIGCSE董事会任职。
Dr. Daniel Zingaro is an Associate Teaching Professor at University of Toronto. He has taught introductory Python programming to thousands of students over the past 15 years and wrote the Python textbook that is currently being used for the course. He has also written dozens of research articles about how to teach and learn introductory CS. Dan has written two books with No Starch Press—the aforementioned one on Python and one on algorithms—that have been translated into multiple languages. Dan has received several prestigious teaching and research awards, including a 50-Year Test of Time award and multiple Best Paper awards.
丹尼尔·津加罗（Daniel Zingaro）博士 是多伦多大学的副教授。在过去的 15 年里，他向数千名学生讲授了 Python 编程入门课程，并编写了这门课程目前下在使用的教科书。他还撰写了数十篇关于如何教授和学习计算机科学入门课程的教研文章。丹尼尔与 No Starch Press 合作出版了两本书——上述的 Python 教科书和一本关于算法的书籍——这两本书均被翻译成多种语言。丹尼尔获得了多个著名的教学和研究奖项，包括一个 50 年时间考验奖和多个最佳论文奖。
About the technical editor
关于本书的技术编辑
Peter Morgan is the founder of the AI consulting company Deep Learning Partnership based in London (www.deeplp.com). He has an advanced degree in physics along with an MBA. He has been working in AI for the past ten years and before that spent ten years as a Solutions Architect for companies such as Cisco Systems and IBM. Peter has written several reports, papers and book chapters on AI, physics, and quantum computing. He consults on LLMOps and quantum computing for startups and enterprises globally. You can follow Peter on Twitter (@PMZepto).
彼得·摩根（Peter Morgan）是位于伦敦的人工智能咨询公司“Deep Learning Partnership”的创始人。他拥有物理学的高级学位以及MBA学位。在最近十年里，他一直在人工智能领域工作；在此之前，他曾在Cisco Systems和IBM等公司担任解决方案架构师达十年之久。彼得撰写了多份关于人工智能、物理学和量子计算的报告、论文和书籍章节。他为全球的初创公司和大型企业提供LLMOps和量子计算领域的咨询服务。想要了解更多彼得的见解和动态，可以在推特上关注他的账号（@PMZepto）。