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.
About this Course
Skills you will gain
University of Washington
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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TOP REVIEWS FROM DATA MANIPULATION AT SCALE: SYSTEMS AND ALGORITHMS
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.
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.
Great course that strikes a balance between teaching general principles and concepts, and providing hands-on technical skills and practice.
The lessons are well designed and clearly conveyed.
Very good introduction to relational algebra and map reduce. Also helped scratch up on some python and SQL.
About the Data Science at Scale Specialization
Learn scalable data management, evaluate big data technologies, and design effective visualizations.
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