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
It's pretty tough in assignments especially when there are mistakes in the given description, but I do learn the basic concepts of relational algorithm and MapReduce from them.
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.
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.
I like the breadth of coverage of this class. Each of the exercise is a gem in that I get to learn something new also. I would highly recommend this even to experience practitioner also.
Специализация Наука о больших данных: общие сведения
Learn scalable data management, evaluate big data technologies, and design effective visualizations.
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