Data analysis has replaced data acquisition as the bottleneck to evidence-based decision making --- we are drowning in it. Extracting knowledge from large, heterogeneous, and noisy datasets requires not only powerful computing resources, but the programming abstractions to use them effectively. The abstractions that emerged in the last decade blend ideas from parallel databases, distributed systems, and programming languages to create a new class of scalable data analytics platforms that form the foundation for data science at realistic scales.
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Founded in 1861, the University of Washington is one of the oldest state-supported institutions of higher education on the West Coast and is one of the preeminent research universities in the world.
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DATA MANIPULATION AT SCALE: SYSTEMS AND ALGORITHMS의 최상위 리뷰
A great way to start, and become familiar with the nature, requirements & analytics of today's data.
Good! I like the final (optional) project on running on a large dataset through EC2. The lectures aren't as polished and compact as they could be but certainly a very valuable course.
Last week of the course is too much information and without any assignments it kind of doesn't make much sense and it doesn't stick.
Engaging problemset makes sure that you will get your hands dirty with data. And that is great! Definitely worth your time.
대규모 데이터 과학 특화 과정 정보
Learn scalable data management, evaluate big data technologies, and design effective visualizations.
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