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Data Manipulation at Scale: Systems and Algorithms(으)로 돌아가기

워싱턴 대학교의 Data Manipulation at Scale: Systems and Algorithms 학습자 리뷰 및 피드백

754개의 평가
165개의 리뷰

강좌 소개

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...

최상위 리뷰

2016년 1월 10일

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.

2016년 5월 27일

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.

필터링 기준:

Data Manipulation at Scale: Systems and Algorithms의 161개 리뷰 중 1~25

교육 기관: Anne-Marie T

2020년 1월 6일

I don't recommend this course. Even though I learnt a few things, it has not been maintained for a while. It's a pain to fix errors in assignments as automatically corrected solutions may not match the actual correct answers to the questions. And the material is not up-to-date. MapReduce is useful but has been superseded by Spark a few years ago already.

교육 기관: Max E

2018년 11월 12일

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

교육 기관: Toby E

2020년 5월 7일

I did this course about 4 or 5 years ago - since then, I've been lucky enough to have been a data engineer on some truly huge systems, and I use the skills I learnt on this course every day. This was the course that turned me from a data user to engineer. Whenever I'm asked for a data course recommendation, it's this one every time

In particular, the sessions on relational algebra and map reduce gave me a really deep understanding of what was really going on when running queries or jobs. Before this course, if I wanted to write some sql, I would find an old query and just change things round a bit before I got what I wanted - now I generally can write them from scratch (except windowing ones ... they still get me)

It's easy enough to write any old job for a small amount of data - but as the scale increases, so does the time taken, and small problems magnify. That costs you sleep, and your company money. Study this course carefully, and learn how to do it properly for reall

I'm writing this review because I'm recommending the course yet again to another colleague ....

교육 기관: Anish C

2018년 1월 17일

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

교육 기관: Jan M

2019년 6월 17일

The course material is ok, but the support and assignment grading is horrible - I spend several hours just battling with grader after having the results ready. Definitely wouldn't recommend this course to anyone. I subscribed for the whole Specialization and completed Course 1 and 2. Unfortunately Course 2 finishes with Peer Graded Assignment - I submitted it with a few weeks to go before my subscription expires but there was no one to grade it so once my subscription ended I didn't get the certificate despite completing the whole second course as well and I lost access to all my submissions and the Course material even though I have already paid for it.

교육 기관: Daniel W

2017년 4월 26일

For me, a really nice combination of

1. a theoretical overview of database and data processing concepts, MapReduce and the most important implementations of the various concepts (SQL and NoSQL databases),

2. practical application of these concepts in real-world programming exercises.

I like the way Bill explains, and I like the exercises - however, to complete those, you need to be ready to learn the technology on your own, the lectures are NOT about learning the technology (Python programming etc.) to do the exercises. For me, that's fine, but for people who have little or no programming experience it might be frustrating.

So, if you like the combined approach of this course, I can really recommend it!

교육 기관: Christopher A

2015년 9월 29일

It gave a nice, challenging and very engaging introduction to different data preparation techniques. The course surveyed Twitter data stream analysis, SQL, MapReduce jobs and a host of NoSQL and Graph tools. While it could use assignments for the latter topics, the course was structured in an easy to follow manner and was sufficiently challenging to keep engagement. In addition, the way the lessons were broken down into digestable chunks greatly aided in keeping engagement and keeping my interest. I look forward to future courses offered by UWashington and the same professor.

교육 기관: Huynh L D

2016년 6월 30일

I had a lot, really, a lot of fun in this course.

The first week was really awesome! Although the debugging was very tedious and time-consuming, I felt a great deal of achievement first hand dealing with Twitter data and coded up text analytics algorithms from scratch.

Really a great introductory course to data science! Highly recommend because it's really fun. However, a great amount of comfort with coding and patience for working through ambiguous bug messages will be essential to completing this course :)

교육 기관: Valery N

2017년 9월 2일

Excelente curso, contenidos muy completos; sin embargo, deberían actualizar las instrucciones de cada Assignment con las correcciones ya descritas en los foros, para algunos es díficil encontrar estas correcciones fuera del enunciado. Por lo demás, gracias por esta oportunidad, por abrir las puertas de una universidad tan importante a otros estudiantes que jamás podrían asistir a su campus.

교육 기관: Sofia C

2016년 11월 14일

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.

교육 기관: Zahid P

2015년 11월 14일

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).

교육 기관: Korbinian K

2016년 11월 7일

Really useful course when you want to learn about big data management and need a starter. It is however definitely recommended to have some programming experience and knowledge about bash/command line. The course met all my expectations, but to make it perfect I would have wished for an extra exercise using Pig or Spark.

교육 기관: Jakub B

2016년 1월 4일

Really good teaching: instead of cramming tons of information lecturer differentiates main ideas from technical stuff (that will surely change in several years). Also, exercises are good.

Disclaimer: I have browsed several courses that touch these topics. I think this one is the best, at least on coursera.

교육 기관: Francisco J

2017년 3월 6일

Overall, this was an excellent introductory course. The instructor presented the material in a very clear manner and introduced all topics using applied examples. The weekly assignments were aligned with the course content as well, allowing me to apply the knowledge learned in each lesson.

교육 기관: Robert H S J

2016년 2월 15일

I learned so much from this course. In particular, I've got a much more solid grasp of SQL (even though I've been using it for 30 years), and much more clarity about "map/reduce". The lectures are clear, delivery is excellent, and the assignments are interesting.

교육 기관: Mangesh J

2015년 9월 27일

Awesome course. I would love more courses like this.The only part I feel rather discomforting is that the course does not offer non verified certificates to those who cannot afford the 59 dollar fee (PS from India and 59 dollar for a course is huge deal for me) :)

교육 기관: Vijai K S

2016년 1월 19일

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.

교육 기관: Kairsten F

2016년 9월 22일

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.

교육 기관: Maria P

2015년 10월 28일

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.

교육 기관: Qianhong H

2019년 9월 9일

The lecture covers a broad range of materials, from complexity of algorithm to map reduced formulation. The assignments are challenging and up to date. However, I would prefer the lecture to be more technical and coherent.

교육 기관: Kenneth P

2015년 12월 6일

Course is well structured, moving on with the lessons is a build up of techniques and concepts. Delivery of the course material is well paced and gives all the required information to grasp the concepts.

교육 기관: Paulo S S S

2016년 2월 6일

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.

교육 기관: Hernan A

2016년 1월 11일

Great course that strikes a balance between teaching general principles and concepts, and providing hands-on technical skills and practice.

The lessons are well designed and clearly conveyed.

교육 기관: Dimitrios K

2016년 1월 24일

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.

교육 기관: Benjamin T

2016년 2월 25일

- great and very useful overview of concepts important in big data that does not get bogged down in random details

- interesting and sufficiently challenging assignments