Aug 24, 2019
Introduction of ML for Financial application with combination of Scikit learn, Statsmodels and Tensorflow with neuralnets made this class very interesting. Learned and Enjoyed lot.
May 28, 2018
Exceptional disposition and lucid explanations! Ideal for a Risk Management professional to sharpen machine learning skills!
von Alexander R•
Oct 17, 2018
Assignments were whack...
von Roland E•
Jan 09, 2020
The assignments and project are very briefly explained. It took me a lot of unnecessary time to figure out what I was supposed to do. Also the discussion forum is inactive and I have a feeling many leave after seeing not anyone respond to their questions. I think there should be one or two dedicated support answering questions at least within 3 days.
The level of the course in general is pretty high, definitely not beginners level, which is fine I guess, but I do find the lectures are at times going very quick and at times overcomplicate. I would prefer an example to start simple and from there to build for a more complex situation. (For example start the bank failure with say 3 main features and show how you can decide to add another one by showing its impact through deviance and multicollinearity and show how you can then decide to add this new feature or not.)
von Fabien N•
Jan 12, 2020
Actually I was finding that course amazing at first, but I gradually became very upset. The notebooks are way too high level and not self-explanatory. The teacher seems amazing by his knowledge, but one are left with the notebooks without knowing what to do, and the lectures only partially help to solve the problems. A lot of search online needs to be done and I don't think that is the spirit of Coursera courses. I was planning to pay for the whole specialization but unfortunately I will have to give up on this course that was very motivating at first...
von Ruixin Y•
Jun 18, 2018
Spent more time than expected. And when I tried to access the last assignment, it showed "404 : Not Found You are requesting a page that does not exist!"I understand the professor and other TA put a lot of effort on these courses, but I would say the assignments are not well organized, and more instructions are needed. Really hope the instructors could update/improve the courses/assignments. Thanks.
von Debasish K•
Feb 26, 2019
Good because it gives a high level good overview of ML in Finance, SVM and Tensorflow.
However, Some examples are very easy and some have been made difficult by providing no references. Tobit regression was very vague. No links to proper reference. Neural Network was the example from Geron's Handbook but there were errors in the custom function that was defined.
More mathematical depth is required.
von Vincent L•
Aug 25, 2019
extremely hard to follow, but better than when it originally came out. I had signed up after numerous ML courses and tried to skip to the later courses in this specialization. I got stuck trying to implement some crazy equations. I'm ok with looking up api methods, but the need to look out for reshaping is troublesome because it's inconsistent throughout the course. Overall, hard to follow.
von Desi I•
Sep 18, 2018
Good overview of ML and some basic applications to finance.
The pace is very good for people with some training in statistics and maths.
The assignments, however, are not particularly clear and with some obvious errors. There's room for improvement in the description of the exercises as well as including some tests to verify that you're getting the correct output.
von cyril c•
Oct 11, 2018
content of the lessons is quite good, I would give it 5 stars if the assignments weren't so buggy, contains mistakes, unclear instructions, no help from staff/moderator/instructor, technical issues that are not resolved, etc. a lot of frustration, it just feels like the course was rushed to production and they let the students debug it
von Umendra C•
Nov 18, 2018
Course material is good and a rating of 4 stars or more would have been a fair one, if it was not for very poorly designed and ill prepared assignments. The teaching staff really need to step up a level or two for the assignments.
The course content is good and that the only reason, I am still sticking with this specialization.
von Shobhit L•
Aug 06, 2018
The assignments can improve a lot. The jupyter notebooks have no clarity in instructions and most of the time we have to struggle to find exactly what is expected from our code.
The specialization has a lot of potential, anchored only by the lack of the quality of the assignments.
Sep 22, 2018
It's a good course but the homework is poorly designed with unclear instructions. Moreover, it's better to get familiar with Python before start this course. The suggested book "Hands-On Machine Learning with Scikit-Learn & TensorFlow" is a very good resource.
von Philipp P•
Oct 06, 2018
Cons: overall content is good. Pros: when you release something (software or scientific article) you often do rigorous testing. Why not to do it with your Jupyter Notebooks? I do not understand it.
von Mike S•
Jan 04, 2020
The lectures were very good, but the assignments lacked supporting material. Also, most of the further reading was behind a paywall or the links had been removed.
von Vincent G•
Nov 20, 2018
Content of the class is really good but technology/support is deplorable (Had to wait 3 weeks before the assignments got fixed by the support staff)
von Vitalii A•
Dec 10, 2018
Not very related to finance plus most of the tasks are easy to complete, but hard to understand what needs to be done.
von Alan X•
Jul 29, 2018
There is always something to be fixed in the assignments... Great content and relevance though.
Aug 31, 2018
Great content, but the labs are difficult to understand and often unrelated with the content.
von Lee H C T•
Sep 23, 2018
some python notebook has bugs, wasting time for me to fix
von Vicente I•
Dec 20, 2018
It lacks information on how to proceed on NN coding.
von Masato Y•
Apr 14, 2019
von Amro T•
May 19, 2019
This course is more of mathematical introduction to machine learning than actual practical machine learning tips and tricks course. Math is definitely crucial but the way it was conveyed was not really good. I would have provided a refresher week just in math to refresh the students before jumping into the mathematics in the course. In the notebooks, there is a lot that was missing. Because I was already familiar with the material and I used TensorFlow, Numpy, Sklearn and statsmodels before and built several models with them before, I was able to navigate through. But if I was a totally new student, I would have a very hard time going through those notebooks. A couple of good notes, Please try to summarize all the important equations into a PDF file either for the entire course or per week to be as a reference when needed.
von Ricardo F•
Jul 22, 2018
I gave up while working on week 4's homework of the first course of this specialization. The two main reasons that led me to do so are: (1) very little on finance engineering except reference to problem cases and recommended readings; and (2) homework quality is really inferior to other machine learning courses I took at Coursera. I recognize that my first observation may not apply to the remaining courses of this specialization, but it is definitely the case in course 1. In the end, I thought I was not learning enough to justify the time and effort. Lectures are OK but they could be improved a lot by adding more financial engineering elements.
von Serg D•
Dec 03, 2019
This course is highly academic and has nothing to do with the finance. The only realistic dataset used was for the final project. No resources provided, just names of articles and book chapters. Where am i supposed to get them from? The course does not have the practical part at all. It goes like this: you get 1 hour of videos with formulas and then supposed to write code. HOW????!
von ALI R•
Aug 19, 2019
The course material are presented sparsely despite my initial expectation which may be formed by Andrew Ng in his ML course. Anyway I believe it is a good roadmap for learners of ML in finance and also for me to find and I should be grateful of the Coursera.
von Hrishikesh A R•
Jun 23, 2019
Objectives of assignments are not clear. The instructions provided in assignments are not clear. Tensorflow should be taught extensively because most of the students are facing problems in same.