The course was well designed and delivered by all the trainers with the help of case study and great examples.\n\nThe forums and discussions were really useful and helpful while doing the assignments.
Very good overview of ML. The GraphLab api wasn't that bad, and also it was very wise of the instructors to allow the use of other ML packages. Overall i enjoyed it very much and also leaned very much
par Ravi P•
The materials used in this course are extremely outdated. In order to access the data to do the projects you have to use SFrame, which is only supported up to Python 3.4.x. Python is currently on v 3.7.0. The data should be provided as .txt or .csv to be more universal. The instructors claim that you don't have to use a specific library to do this course, but you have to have at least SFrame in order to access the data! Further I am sure SFrame and Graphlab are good tools, but the course should be taught with open source tools so that the students can continue to use those tools after the course is over.
I wanted to like this course. I did enjoy the professor's teaching styles, but the fact that I would have to download a new outdated python environment, and non universally accepted tools, to even access the data is a major deal breaker!
par Oscar R•
I spend two days trying to get the graphlap lib working on two OS, and could not. I had to spend couple of hours setting up the aws services to be able to work with the samples.
Phd's I dont think they make good teachers....
par Ibrahim M A•
My only happiest moment in this whole course is writing this review, I couldn't wait to finish it in order to give it the 1 star rating it deserved.
What I've seen from this course so far is abandonment , that's right this course is abandon ware, no questions get answered on the forums (asked a question a month ago and still didn't get an answer) and the links are outdated (links to further documentation don't work).
I wouldn't recommend this course to anyone wanting to learn Machine learning since the instructors use proprietary libraries that need a license to use outside this course thus application wise what you learn her isn't transferable only the conceptual content;however, even in that there isn't much content for, since everything is an introduction here so nothing is quite useful .
If your on a tight budget and your taking this specialization you could skip this course. Actually you could even skip this specialization since they canceled the capstone project so investing any money and time here is a waste. I can only recommend this specialization/course IF the instructors add a project at the end , be more involved on the forums , update non functional links ,and finally USE NON PROPRIETARY libraries hence they will need to take feedback from the students and redo most components of this specialization.
par Jatin K P•
To follow along the course you need to install Graphlab library, which is the biggest challenge. Also, the support you get from the creators are not good enough.
I regret to waste my time on this course.
par Sourav S•
Too dependent on Sframes and graphlab which does not work most of the times. I had to spend an entire day just figuring out versions of python to make this work.
par sreeraj c•
Such a bad presentation with no help to people with graphiclab tool setup.
par Andrew W•
Requires software called Graphlab Create that would not install on my machine. Unable to complete any of the course material due to this.
par Elvin V•
The worse course I have ever taken on Coursera. Forcing you to use their own library which is also not open source and free is ridiculous! You will never use graphlab in the future and there are better alternatives available! Totally useless experience. And most of the time vide lectures are just some mumbo jumbo, like showing diapers or napkins for 2 minutes! I have successfully wasted a lot of time on this course.
par Ernie M•
I enrolled in this specialization to learn machine learning using GraphLab Create. Half way into the specialization the creators sold Turi, GrapLab's parent company, making it non available to the general public (not even by paying) and then all the knowledge devalued. I wish I had known this and I would have enrolled on a different specialization. The creators still give you the possibility of using numpy, scikit learn and pandas but I had already done a lot with GraphLab create. The time I invested on my nights after work became a waste. I was trying to convince the company I worked for to buy licenses for GraphLab create.
Coursera should not allow folks to create courses that promote a private license course because it would make people waste their time and money if they decide to privatize the software.
Don't take this course, and if you take it then only use GraphLab create when the authors give you no other option.
Teaching style: Carlos was good, Emily is not very clear and loses focus of the topics and often rambles. She seems very knowledgeable but she lacks clarity of exposition when compared to Carlos or Andrew Ng.
par Gianmaria M•
Very relevant material clearly explained by the professors, who are very knowledgeable and engageing. However the installation and usage of the GraphLab module is cumbersome and plagued with bugs. This could still work if there was enough support however I did not find any helpfrom the mentors/tutors who simply did not answer my questions in the Forum thus making my experience even more frustrating. Pity, I certainly hope Coursera can fix it as the class is quite good
par Muhammad W K•
A great course, really designed to understand the underlying core concepts of machine learning using real-life examples which takes you through all that with little to no programming skills required!
par Sharina C•
I am extremely frustrated with this course. I have spent sooo many days just trying to get the software set up. It's currently week 3 and I can't complete week 1. I've followed the directions and run in numerous roadblocks, some of which I was able to resolve after searching through the course forums. I shouldn't have to scour the forums to get setup...the instructions should be updated. Unfortunately, I'm still stuck in week 1, unable to get the software running properly. It's really frustrating.
Maybe a good course, but you need to be an IT crack to be able to install the software and make it works. Online help does not help. Irritating! 45USD lost. I don't recommend this course.
par Rahul D•
Course uses proprietary packages. Better learning from "The Analytics Edge" conducted by MIT at Edx.org
par Walther A G L M•
relying on proprietary library and unreliable notebook made this experience painful
par Matthew H•
I just completed the first week of this course and am choosing not to continue. The first week consisted of 75 minutes of video in which we learned a half dozen facts regarding Python syntax and the use of SFrames. This content could have been presented in a single 5 minute video with just a little planning and editing. I realize that the presenters perhaps wanted to ease folks in, but this is silly. There may be good content in the following weeks, but I am not patient enough to find out. Gonna try a different ML class. Sorry guys.
par Mike C•
The course is basically an advertisement for the software one of the teachers created. I did learn a bit of high level concepts, but when it comes to coding, the answers is always 'conveniently, my software does this for you'. I wanted to actually learn about these concepts deeper, and implement them.
I also was able to complete this 6 week paid course in a few days which should not be possible. I have since started the free Stanford course taught by a co-founder of coursera, and it is MUCH better! I recommend it to anyone!
par Theron R F P•
Good intro to the ML concepts, but my review is negative due to :
par lianghui t•
the graphlab can not be installed
par Shane C•
I did not find the course very good. I came into the class with only real basic knowledge of Python and I was hoping to be able to pick up more as part of this class. WHile I might have picked up more, it was only because I used resources outside the course.
The video instructions in programming in Python left quite a few gaps to figure out by reading documentation. The videos themselves were divided into two sections -- first a theoretical or classroom like section and a second a lab/programming section going over some coding in Python. The 'classroom' type lectures were pretty reasonably good. But the lab/programming were pretty terrible.
They instructor really break down the syntax of the code and just left the student to figure it out. This made being able to take this code and to adapt it to other uses very difficult.
I would not recommend this as a course to help learn Python.
par Eugene K•
If you are considering this specialization I would recommend the Andrew Ng course instead and the main reason is that it isn't depend on proprietary ML framework. Despite the good lectures, the assignments don't help you develop the knowledge required for ML developer role.
Taking in consideration the permanent postponing the courses delivery, from summer 2016 to summer 2017, finally the most interesting part of the specialization was cancelled. I'm completely disappointed with the specialization learning expirience.
par Pritish K•
The most useless course on Coursera. I have wasted 3 weeks just trying to install Graphlab and the installation seems infinitely tedious. There is no support from Coursera or University of Michigan to install the software
Why do they insist on teaching on a software which have so many known issues and so many students are struggling to install the software.
The objective is to learn data analytics and machine learning, not to become a systetm admin and n IT guy.
par Valentin T•
Using a proprietary library instead of widely used libraries and discouraging the use of open source widely used libraries. It barely compiles, the example notebook has method calls that use non existing methods of the SFrame object.
The course claims that it teaches the student how useful practical knowledge but then ends up using a non standard library and saying not to use pandas or scikit learn.
par Sam Z•
Emily and Carlos teach this class in a very interest way. They try to let student understand machine learning by some case study. That worked well on me. I like this course very much.
par Florian M H•
I am a professional SW developer (Embedded C for control units). I do not recommend this course for people who already know something about machine learning. If you want to learn the basics of ML, Stanford's Machine Learning course is a far better choice (is based on Matlab though).
This one here has far too little content.
Moreover, in case you cannot install the needed GraphLab/TuriCreate SW package (only MacOS or Unix, for Windows not always working, as for me also!) then you're basically left alone with finding a) the SW packages you need (I took scikit, numpy, pandas) and the corresponding commands (because the entire course explains ONLY commands for Graphlab, NOT for the other packages) - this is BIG extra work you need to do on your own. Now the big joke is that all other courses in the specialization are NOT based on Graphlab, but on the other packages I mentioned ;).
In addition: Literally 0 support from teachers/mentors in the forum during the course. The students have/had to handle most/all problems themselves. This is a no-go.