교육 기관: Kevin M•
Little instruction occurs during this course - basically you will teach yourself from an intermediate-level smattering of lessons, the quizzes cover topics not covered in the materials, assignments appear to contain errors, and there is effectively no support from the teacher or assistants.. the vast majority of questions are unanswered.
Poor execution of what otherwise appears to be worthwhile content and material.. if you get stuck, you are toast!
I would be embarrassed if I were a University of Illinois alumni. To those charged with oversight: you need to adequately support this course in its current format or redevelop.
교육 기관: Ryan B G•
I have very mixed thoughts about this course. I made it through the course and definitely understand data analytics much better than when I started. However, here are my complaints:
- The class seems to have been abandoned by the University of Illinois and Professor Brunner. There haven't been any replies or posts in the discussion board from any staff for one year, despite the fact that there are various typos and errors in the Jupyter notebooks. This is truly a self-guided course.
- It's difficulty is listed as "beginner" and there are no prerequisites. However, I had to pause the course to go learn Python on Codecademy and then finish a full Python specialization here on Coursera before feeling like I knew it well enough for this course. And then I had to pause the course again to go learn NumPy and Pandas over at dataquest.io. Yes, all of these things are taught in this course, but they are taught so quickly and with very few practice opportunities, that it is really hard to master the skills prior to moving onto the next step.
- Besides Python, NumPy, and Pandas, I recommend that you have a pretty good handle on statistics before taking this course.
- And my final complaint is that this course really never teaches you anything about accounting. A few articles are shared for you to read through, but none of the data analytics examples use accounting data. The dataset that is most frequently used in this class involves the petal and sepal widths and lengths of three different types of Iris flowers.
교육 기관: S. U•
Awful course. Zero actual instruction. The videos are 4-5 minutes of someone blathering on while scrolling over a Jupyter notebook saying "here's the notebook you'll be working on, but we're not going to explain anything". There is absolutely *zero* accounting-related content. NONE. Queries from students have been ignored for months - in fact, years. Weird grading errors means you won't be able to submit assignments, but you only get the completion certificate if you pass all assignments. Which you can't.
The university should be embarrassed. My impression of GIES is that it's filled with incompetent, lazy, greedy instructors that simply keep this awful course up as a money-grab. Coursera needs to take this course down.
교육 기관: Vijay G K•
Amazing course in terms of design, content. I was badly searching for a course in Data Analytics for Accounting Professionals. This course fits the right content needed to start of ones basics in learning Python and then seamlessly integrates into Accounting Profession. Thanks to amazing professor, he makes the solid content look easy to grasp.
교육 기관: Paul V•
This is a great course to expose you to a lot of different topics. I've gotten more comfortable with Python, and have a number of topics to draw from when thinking through how to analyze financial data. This is a must if you want to become a better analyst.
교육 기관: ARVIND K S•
One of the most under-rated courses on Coursera. It really tests you and forces you to learn, albeit at your own pace, depending on whether you're a beginner or an expert in the subject. It really opens up an entirely new world for accountants.
교육 기관: Chinmay S M•
Nice way to get started on the career path of Data Analytics. Thank you Prof. Brunner.
교육 기관: RITIK S•
Very good for beginners.
교육 기관: Nyam-Ochir B•
교육 기관: shan•
This course is difficult for the beginner.
교육 기관: Deleted A•
I just want to unenroll