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學生對 华盛顿大学 提供的 大规模数据处理:系统与算法 的評價和反饋

4.3
746 個評分
161 條評論

課程概述

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...

熱門審閱

HA
2016年1月10日

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.

WL
2016年5月27日

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 - 大规模数据处理:系统与算法 的 25 個評論(共 157 個)

創建者 Anne-Marie T

2020年1月6日

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.

創建者 Max E

2018年11月12日

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

創建者 Anish C

2018年1月17日

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

創建者 Jan M

2019年6月17日

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.

創建者 Toby E

2020年5月7日

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 ....

創建者 Daniel W

2017年4月26日

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!

創建者 Christopher A

2015年9月29日

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.

創建者 Do H L

2016年6月30日

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 :)

創建者 valery n

2017年9月2日

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.

創建者 Sofia C

2016年11月14日

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.

創建者 Zahid P

2015年11月14日

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).

創建者 Korbinian K

2016年11月7日

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.

創建者 Jakub B

2016年1月4日

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.

創建者 Francisco A J

2017年3月5日

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.

創建者 Robert H S J

2016年2月15日

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.

創建者 Mangesh J

2015年9月27日

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) :)

創建者 Vijai K S

2016年1月19日

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.

創建者 Kairsten F

2016年9月22日

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.

創建者 Maria P

2015年10月28日

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.

創建者 Qianhong H

2019年9月9日

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.

創建者 Kenneth P

2015年12月6日

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.

創建者 Paulo S S S

2016年2月6日

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.

創建者 Hernan A

2016年1月11日

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.

創建者 Dimitrios K

2016年1月24日

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.

創建者 Benjamin T

2016年2月25日

- 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