HN Academy

The best online courses of Hacker News.

Hacker News Comments on
Data Manipulation at Scale: Systems and Algorithms

Coursera · University of Washington · 1 HN comments

HN Academy has aggregated all Hacker News stories and comments that mention Coursera's "Data Manipulation at Scale: Systems and Algorithms" from University of Washington.
Course Description

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.

In this course, you will learn the landscape of relevant systems, the principles on which they rely, their tradeoffs, and how to evaluate their utility against your requirements. You will learn how practical systems were derived from the frontier of research in computer science and what systems are coming on the horizon. Cloud computing, SQL and NoSQL databases, MapReduce and the ecosystem it spawned, Spark and its contemporaries, and specialized systems for graphs and arrays will be covered.

You will also learn the history and context of data science, the skills, challenges, and methodologies the term implies, and how to structure a data science project. At the end of this course, you will be able to:

Learning Goals:

1. Describe common patterns, challenges, and approaches associated with data science projects, and what makes them different from projects in related fields.

2. Identify and use the programming models associated with scalable data manipulation, including relational algebra, mapreduce, and other data flow models.

3. Use database technology adapted for large-scale analytics, including the concepts driving parallel databases, parallel query processing, and in-database analytics

4. Evaluate key-value stores and NoSQL systems, describe their tradeoffs with comparable systems, the details of important examples in the space, and future trends.

5. “Think” in MapReduce to effectively write algorithms for systems including Hadoop and Spark. You will understand their limitations, design details, their relationship to databases, and their associated ecosystem of algorithms, extensions, and languages.

write programs in Spark

6. Describe the landscape of specialized Big Data systems for graphs, arrays, and streams

HN Academy Rankings
Provider Info
This course is offered by University of Washington on the Coursera platform.
HN Academy may receive a referral commission when you make purchases on sites after clicking through links on this page. Most courses are available for free with the option to purchase a completion certificate.
See also: all Reddit discussions that mention this course at reddsera.com.

Hacker News Stories and Comments

All the comments and stories posted to Hacker News that reference this url.
HN Academy is an independent project and is not operated by Y Combinator, Coursera, edX, or any of the universities and other institutions providing courses.
~ [email protected]
;laksdfhjdhksalkfj more things
yahnd.com ~ Privacy Policy ~
Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.