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 MapReduce is useful but has been superseded by Spark a few years ago already.

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 ....

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

This course offers a mixed learning experience:

pros:

(1) some lessons offer deep understanding of SQL and MAP REDUCE algorithms.

(2) the HW is challenging and gives you an opportunity to actually implement SQL, DATA MINING, and MAP REDUCE. (con: those areas are big, and this course only slightly touches each)

cons:

(1) the tasks are very hard, simply because they are written bad(!!!!) : there are discrepancies between the written task and what the Automatic grader checks, insufficient documentation, weird way to submit points among the problems, weak help from mentors (if at all). boy, I found myself pulling my hair out.

(2) this course takes it for granted the you already know SQL, and how to work with linux based OS in a virtual box, and of-course: python is a must. If you are new to one or more of those subjects, this might not be the course for you.

(3) the talks offer very little help in solving the tasks. so basically you are on your own and need to search for clues in the web or read out comments from other desperate learners.

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

Incredibly outdated (2015), material courses and videos are low quality.

Hands on resources have not been updated in years (scripts use deprecated Twitter APIs using deprecated versions of Python). Students should spend time learning and experimenting, and not patching poorly written and poorly maintained scripts all over the course.

Truly dissapointed.

The start is very "dry" lot's of information about what Data Science is. You cant start with the first assignment, because the script and tutorial is outdated. It simply doesnt work

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.

The assignments depend on an obsolete version of Python; it would be simple to update the course to use a version of Python that was easily available. I am having difficulty setting up a machine, real or virtual, that will let me complete the assignments, or even just installing Python 2.7 on my usual machine. Rather than go through a lot of hassle against a deadline, I'm just going to set this whole idea aside and maybe just read up the topics on my own.

The instructors do not respond and they provide computer programs that do not work. They are aware that there are issues in the programs but have done nothing to remedy the issue.

Has not stayed on top of changes to Twitter API, forums are not useful, and still uses Python 2! This course badly needs to be updated and is not usable in its current form.

This course is very out of date. The assignments need to be updated to address changes to Twitter API and Python.

I strongly recommend you move this course to a platform better than coursera.

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.