Working through the entire course provides comprehensive coverage of the field, but most of the topics are also well-suited for "a la carte" learning. Her research interests span many aspects of nontraditional data management. Codd Innovations Award in and was a Guggenheim Fellow in ; she has served on a variety of program committees, advisory boards, and editorial boards. The course material is scheduled for just over 9 weeks, followed by a final exam period March , Each week includes hours of video material, although some students review videos multiple times, while others opt to crank up the speed.
Quizzes and exercises can vary from attempting the minimum number of problems just once perhaps a couple of hours , to repeating all of the required and optional problems until you have them completely nailed. The course does not assume prior knowledge of any specific topics, however a solid computer science foundation -- a reasonable amount of programming, as well as knowledge of basic computer science theory -- will make the material more accessible.
Also bear in mind that picking and choosing which topics to learn is a great approach, and not all topics require the same level of background. Detailed lecture notes are provided. Having a textbook in addition to the notes is not necessary, but you might want to purchase one for reference, to reinforce the core material, and as a source of additional exercises.
Suggested textbooks and readings are listed as part of the materials. Stanford students watch exactly the same videos and do exactly the same quizzes and exercises. In addition, Stanford students work hand-graded "challenge problems" in certain topics, and they have a multi-part programming project. We expect to use a similar metric this year. Stanford University pursues the science of learning. Online learners are important participants in that pursuit.
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