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.
Об этом курсе
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.
- 5 stars57,25 %
- 4 stars25,46 %
- 3 stars9,10 %
- 2 stars4,61 %
- 1 star3,56 %
Лучшие отзывы о курсе DATA MANIPULATION AT SCALE: SYSTEMS AND ALGORITHMS
This is a quite wonderful course for large-scale data science. I believe I will have learned a lot via completing the courses.
Its pretty decent. I liked the assignments. However there were some typos in the lecture slides and also the grader output is not very friendly.
Definitely need some background in R or Python and the lectures are a bit old. Seem to be from around 2013 when this first came out but most of the info is still relevant.
covers a lot of ground quickly, but you still get a good understanding of the underlying theory or technologies
Специализация Наука о больших данных: общие сведения
Learn scalable data management, evaluate big data technologies, and design effective visualizations.
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