Avis et commentaires pour d'étudiants pour Data Manipulation at Scale: Systems and Algorithms par Université de Washington

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 MapReduce is useful but has been superseded by Spark a few years ago already.

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

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

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.

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 ....

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!

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.

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 :)

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.

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.

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).

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.

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.

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.

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.

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) :)

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.

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.

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.

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.

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.

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.

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.

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.

- 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