Learner Reviews & Feedback for Data Analysis with Python by IBM

Really intensive module. Be prepared to learn a lot here. You'll be diving into real stuffs that wil ask you to listen carefully and understand the matter. My advise is to take note of any points that you are not comfortable with and make additional research on google/youtube to become friendly with it.

One of the top module i've complete so far on Coursera. Full of usefull, meaningfull information and knowledge.

Great course, that builds up and ties together some earlier parts of the DS certification. It helped me to understand the process behind developing a model and then later evaluating it. Solid introduction to analysing data with Python and I look forward to applying the skills I learn here in the applied capstone project!

Really great! Tons of information complemented with exercises. To deal with the amount of material, I suggest following the labs very closely and doing a bit of research in the Python documentation avalaible online. I have to say you really hit the core of the matter in this course!

I liked so much that I solve more short test because it helps me to remember information easily and guess it allowed me to perform better. It's the first time I get 100% three times in final tests of each week.

The courses from IBM on Data Analysis, Visualization, Machine Learning are great. I am in an online M.S. program, and the material from IBM is lightyears ahead of my university material.

I have been looking for a very non-complicated course on data analysis and I hit the Jackport with this course! Very simplified and explanatory. You should definitely take the course

Great course. I had fun having a kick start in the field of data in machine learning. I understood the concepts related to how to improve the model.

Thank you

Great Course. Amazing Work By the team. Concepts explained clearly, followed by the week end quiz to revise. The Labs Do a great work in helping out

helps me a lot! FYI I was new to data science and programming language but this course helps me to understand business analysis with Python!

Covers a lot of ground but the Python Labs are great at bringing everything together.

A very complete course of Data Analysis.

Tough but useful.

The course content is definitely interesting, but the approach is superficial. You will get a broad overview of the keyword to search for, and what is available in popular Python packages. However, the quizzes are way, way too easy. The course needs a final "open" assignment, where you have to use the tools without being guided along the way. This is the only way to truly learn.

Course was great but it had number of errors and typos, that per my experience and other attendees caused some confusion.

I am sharing so it could be improved as it is a dream come true for myself to gain this valuable knowledge as conveniently as possible.

Thank you.

Mahvash Nejad

A very comfortably created course - no stress at all. However all that you can get is become familiar with the data analysis tools. May be that's the point.

I think few more practical exercises or at least references of the same would help better understand the overall fundamentals.

Material covered is useful, but there are a lot of typos and mistakes in the lecture slides and labs.

There could be links to functiones libraries in the lab for a fast check of a function if needed.

I think the quizzes can be in the format of programming required questions.

Some mistakes/ typos in the exercises and slides, but great overall

An assignment should have been included

There where some typos in the labs that could confuse most learners. I didn't feel like the course prepared people for real applications. The final project was quite hard because of this .

But it does give you a wide vision on hoy pandas work and some basic but apparently often used tools.

I see this course as a complement to a more detailed data analysis resource or perhaps as simply as an introductory view.

Hello,

in this course there were some errors on the slides, and some quite complicated topics (almost every time related to statistics) was given in a very over-viewed way. Also, some of the python codes were not explained very well, with some terms of them seem to be kind of arbitrary for those who are beginners in the language. My impression is that this course should be longer and more detailed.

Overall I benefitted the course material as a beginner in python and data analysis. The questions were too trivial but maybe that helped me remain engaged with the course and complete it in a short time frame. There were some bugs, typos and minor quality issues that did not really effect my overall experience.

Many typos in videos, stats explained on a very rudimentary way (and often inaccurate), Watson environment is awful as it takes ages for some simple regression plots to be made, it freezes and the interface is not user-friendly, yet we have to use it.