The course is based on the text Mining of Massive Datasets by Jure Leskovec, Anand Rajaraman, and Jeff Ullman, who by coincidence are also the instructors for the course.
An Advanced Computer Science Course by Stanford Online
Welcome to the fascinating world of Mining Massive Datasets, an advanced-level computer science course offered by StanfordOnline. This comprehensive course is based on the groundbreaking text "Mining of Massive Datasets" by Jure Leskovec, Anand Rajaraman, and Jeff Ullman, who also happen to be your esteemed instructors. Dive deep into the realm of big data analysis and discover cutting-edge techniques to extract valuable insights from vast amounts of information.
In this course, you'll gain expertise in a wide array of data mining techniques and algorithms essential for handling massive datasets. You'll master the intricacies of MapReduce systems, explore locality-sensitive hashing, and delve into algorithms for data streams. The course will equip you with skills in web link analysis using PageRank, frequent itemset analysis, and clustering techniques. You'll also learn about computational advertising, recommendation systems, and social network graph analysis. Additionally, you'll explore dimensionality reduction and various machine learning algorithms tailored for big data.
This course is designed for graduate students and advanced undergraduates in Computer Science. To succeed, you should have a strong foundation in:
While a detailed syllabus is not provided, the course closely matches the content of Stanford's CS246 course and covers the following major topics:
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