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
- 5 stars57.23%
- 4 stars25.39%
- 3 stars9.07%
- 2 stars4.73%
- 1 star3.55%
TOP REVIEWS FROM DATA MANIPULATION AT SCALE: SYSTEMS AND ALGORITHMS
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.
This is a quite wonderful course for large-scale data science. I believe I will have learned a lot via completing the courses.
Course gives you good overview on different important data science technologies. Hands on labs are important to get the grip on concepts.
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.
About the Data Science at Scale Specialization
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