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Opiniones y comentarios de aprendices correspondientes a Data Manipulation at Scale: Systems and Algorithms por parte de Universidad de Washington

4.3
697 calificaciones
152 revisiones

Acerca del Curso

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...

Principales revisiones

HA

Jan 11, 2016

Great course that strikes a balance between teaching general principles and concepts, and providing hands-on technical skills and practice.\n\nThe lessons are well designed and clearly conveyed.

SL

May 28, 2016

I like the breadth of coverage of this class. Each of the exercise is a gem in that I get to learn something new also. I would highly recommend this even to experience practitioner also.

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1 - 25 de 148 revisiones para Data Manipulation at Scale: Systems and Algorithms

por Max E

Nov 12, 2018

Assignments need to be updated, but the material is solid!

por Anish C

Jan 17, 2018

Thanks for this course.True Parallel computing example would have made it even more awesome .

por Guruswamy S

May 29, 2018

Very wide and fundamentally robust introduction.

por Gokhan C

May 28, 2016

The assignments are really what make this course stand out.

por Itai S

Nov 14, 2015

הקורס נותן חשיפה טובה לכלי העבודה העדכניים. המשימות אינן פשוטות למשתמש המתחיל ודורשות התעמקות אך בהחלט אפשריות

por Anish M

Sep 24, 2015

great exercises and assignments. The course is involving.

por suyang z

Oct 15, 2015

good for people who have some experience in python and SQL

por Paulo S S S

Feb 06, 2016

Very relevant if you want to understand the theories behind data systems and algorithms. I consider it a bit time consuming but completely worth taking into consideration the amount of topics it covers.

por Sebastian O M

Nov 21, 2015

100% Recomendado

por Mahmoud M

Jan 18, 2016

The course is very coherent and comprehensive. It covers only important aspects of the fields. Also, the exercises are very well prepared.

por Vaibhav G

Jun 16, 2017

Awesome content.

por Zahid P

Nov 14, 2015

While I haven't been able to keep up and submit most assignments, the material seems highly relevant and good to know. The videos are helpful and assignments provide good practice.

Note: I am currently a software engineer and have an undergrad degree in Industrial Engineering (so I have some exposure to the concepts in the course).

por Felipe G

Mar 07, 2016

great course! ... congratulations.

por BI C

Jan 21, 2016

Interesting course, good hands-on exercises. very useful course to practice python

por Vijai K S

Jan 20, 2016

Going through the content really scares someone like me. At the same time, i feel that the challenge in doing the assignments will only help me improve well. I would suggest beginners to stay away and get a hold of the basics before jumping into the course.

por Shibaji M

Sep 17, 2015

This is a great course

por Sofia C

Nov 15, 2016

The contents were very relevant and more geared to those with some experience already. The assignments are worth doing. The only problem is that some of the assignments have errors which are only listed in pinned posts in the forum (with a link to a ticket but nothing's been done about it). Still, learned a lot so the on the whole would recommend it.

por Dimitrios K

Jan 24, 2016

Good! I like the final (optional) project on running on a large dataset through EC2. The lectures aren't as polished and compact as they could be but certainly a very valuable course.

por Asier

Nov 21, 2015

Excellent overview of the Big Data field and its relation to eScience.

por Maria P

Oct 28, 2015

4.5 because it was very difficult to access the optional assignments and there was effort expended on reformatting them since the last offering of the course. Otherwise it's an excellent course and I've already been recommending it.

por francisco y

Jan 19, 2016

Great course!

por Dan S R

May 25, 2017

Great work, very satisfied!!

por Miao J

Dec 25, 2015

Great course. Very helpful!

por Usman

Dec 27, 2016

A great course. I would just like more assignments and more information about spark.

por Kairsten F

Sep 22, 2016

This class assumes intermediate-advanced experience coding in Python, so if you are new, you are likely to struggle a lot. The SQL part, however, was taught from a base-level understanding of almost 0 and is much easier for a beginner.