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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規模に応じたデータサイエンス専門講座ワシントン大学（University of Washington）このコースについて
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次における4の1コース
約20時間で修了
英語
字幕：アラビア語, フランス語, ポルトガル語（ヨーロッパ）, イタリア語, ベトナム語, ドイツ語, ロシア語, 英語, スペイン語
習得するスキル
- Relational Algebra
- Python Programming
- Mapreduce
- SQL
柔軟性のある期限
スケジュールに従って期限をリセットします。
共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
次における4の1コース
約20時間で修了
英語
字幕：アラビア語, フランス語, ポルトガル語（ヨーロッパ）, イタリア語, ベトナム語, ドイツ語, ロシア語, 英語, スペイン語
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ワシントン大学（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.
シラバス - 本コースの学習内容
6時間で修了
Data Science Context and Concepts
Understand the terminology and recurring principles associated with data science, and understand the structure of data science projects and emerging methodologies to approach them. Why does this emerging field exist? How does it relate to other fields? How does this course distinguish itself? What do data science projects look like, and how should they be approached? What are some examples of data science projects?
6時間で修了
22件のビデオ （合計125分）, 4 学習用教材, 1 個のテスト
5時間で修了
Relational Databases and the Relational Algebra
Relational Databases are the workhouse of large-scale data management. Although originally motivated by problems in enterprise operations, they have proven remarkably capable for analytics as well. But most importantly, the principles underlying relational databases are universal in managing, manipulating, and analyzing data at scale. Even as the landscape of large-scale data systems has expanded dramatically in the last decade, relational models and languages have remained a unifying concept. For working with large-scale data, there is no more important programming model to learn.
5時間で修了
24件のビデオ （合計122分）
5時間で修了
MapReduce and Parallel Dataflow Programming
The MapReduce programming model (as distinct from its implementations) was proposed as a simplifying abstraction for parallel manipulation of massive datasets, and remains an important concept to know when using and evaluating modern big data platforms.
5時間で修了
26件のビデオ （合計122分）
3時間で修了
NoSQL: Systems and Concepts
NoSQL systems are purely about scale rather than analytics, and are arguably less relevant for the practicing data scientist. However, they occupy an important place in many practical big data platform architectures, and data scientists need to understand their limitations and strengths to use them effectively.
3時間で修了
36件のビデオ （合計166分）
2時間で修了
Graph Analytics
Graph-structured data are increasingly common in data science contexts due to their ubiquity in modeling the communication between entities: people (social networks), computers (Internet communication), cities and countries (transportation networks), or corporations (financial transactions). Learn the common algorithms for extracting information from graph data and how to scale them up.
2時間で修了
21件のビデオ （合計91分）
レビュー
- 5 stars57.33%
- 4 stars25.49%
- 3 stars9.11%
- 2 stars4.62%
- 1 star3.43%
DATA MANIPULATION AT SCALE: SYSTEMS AND ALGORITHMS からの人気レビュー
RHにより2019年6月30日
A great way to start, and become familiar with the nature, requirements & analytics of today's data.
DGにより2016年1月1日
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.
SKにより2016年1月11日
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.
LGにより2017年6月19日
Comprehensive and clear explanation of theory and interlinks of the up-to-date tools, languages, tendencies. Kudos and thanks to Bill Howe. Highly recommended.
規模に応じたデータサイエンス専門講座について
Learn scalable data management, evaluate big data technologies, and design effective visualizations.
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