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. The book is published by Cambridge Univ. Press, but by arrangement with the publisher, you can download a free copy Here. The material in this on-line course closely matches the content of the Stanford course CS246. The major topics covered include: MapReduce systems and algorithms, Locality-sensitive hashing, Algorithms for data streams, PageRank and Web-link analysis, Frequent itemset analysis, Clustering, Computational advertising, Recommendation systems, Social-network graphs, Dimensionality reduction, and Machine-learning algorithms.
An excellent online course offered by edX: how it works
edX courses consist of weekly learning sequences. Each learning sequence is composed of short videos interspersed with interactive learning exercises, where students can immediately practise the concepts from the videos. The courses often include tutorial videos that are similar to small on-campus discussion groups, an online textbook, and an online discussion forum where students can post and review questions and comments to each other and teaching assistants. Where applicable, online laboratories are incorporated into the course.
edX offers certificates of successful completion and some courses are credit-eligible. Whether or not a college or university offers credit for an online course is within the sole discretion of the school. edX offers a variety of ways to take courses, including verified courses where students have the option to audit the course (no cost) or to work toward an edX Verified Certificate (fees vary by course). edX also offers XSeries Certificates for completion of a bundled set of two to seven verified courses in a single subject (cost varies depending on the courses).
An edX learning programme under Other Experiences
