Data Manipulation at Scale: Systems and Algorithms

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来源：www.coursera.org

8个序列

等级：入门

语言：英语

640分

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80小时总数

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Join the data revolution. Companies are searching for data scientists. This specialized field demands multiple skills not easy to obtain through conventional curricula. Introduce yourself to the basics of data science and leave armed with practical experience extracting value from big data. #uwdatasci

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课程大纲

Part 0: Introduction

Examples, data science articulated, history and context, technology landscape

Part 1: Data Manipulation at Scale

Databases and the relational algebra
Parallel databases, parallel query processing, in-database analytics
MapReduce, Hadoop, relationship to databases, algorithms, extensions, languages
Key-value stores and NoSQL; tradeoffs of SQL and NoSQL

Part 2: Analytics

Topics in statistical modeling: basic concepts, experiment design, pitfalls
Topics in machine learning: supervised learning (rules, trees, forests, nearest neighbor, regression), optimization (gradient descent and variants), unsupervised learning

Part 3: Communicating Results

Visualization, data products, visual data analytics
Provenance, privacy, ethics, governance

Part 4: Special Topics

Graph Analytics: structure, traversals, analytics, PageRank, community detection, recursive queries, semantic web
Guest Lectures

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Bill Howe - Scalable Data Analytics

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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.