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db: Introduction to Databases (Stanford Online) 1 个评论 关注 开始时间: 04/22/2022 持续时间: 未知 主页: https://class.stanford.edu/courses/Engineering/db/2014_1/about 简介: "Introduction to Databases" was one of Stanford's inaugural three massive open online courses in the fall of 2011 and was offered again in early 2013. January 2014 will mark its third offering. The course includes video lectures and demos with in-video quizzes to check understanding, in-depth standalone quizzes, a wide variety of automatically-checked interactive programming exercises, midterm and final exams, a discussion forum, optional additional exercises with solutions, and pointers to readings and resources. Taught by Professor Jennifer Widom, the curriculum draws from Stanford's popular Introduction to Databases course. |
An Introduction to Interactive Programming in Python (CourseraArchive) 5 个评论 关注 开始时间: 04/22/2022 持续时间: Unknown 主页: https://www.coursera.org/course/interactivepython 简介: This course is designed to be a fun introduction to the basics of programming in Python. Our main focus will be on building simple interactive games such as Pong, Blackjack and Asteroids. |
Natural Language Processing (CourseraArchive) 7 个评论 关注 开始时间: 04/22/2022 持续时间: 10 weeks 主页: https://www.coursera.org/course/nlangp 简介: Have you ever wondered how to build a system that automatically translates between languages? Or a system that can understand natural language instructions from a human? This class will cover the fundamentals of mathematical and computational models of language, and the application of these models to key problems in natural language processing. |
Probabilistic Graphical Models Specialization (Coursera专项课程) 0 个评论 关注 开始时间: 12/21/2023 持续时间: Approximately 4 months to complete Suggested pace of 11 hours/week 主页: https://www.coursera.org/specializations/probabilistic-graphical-models 简介: 斯坦福大学 Daphne Koller 教授的概率图模型专项课程系列(Probabilistic Graphical Models Specialization),作为Coursera上最早的几门课程之一,这门概率图模型课程的相当有难度,完成作业拿到证书还是很有挑战的,感兴趣的同学可以关注:Probabilistic Graphical Models-Master a new way of reasoning and learning in complex domains |