Apr 20, 2019
perfect for beginner level. all the concepts with code and parameter wise have been explained excellently. overall best course in making anyone eager to learn from basics to handle advances with ease.
Jul 13, 2018
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
By Everett T•
Jun 29, 2019
The course is overall very helpful to learn Data Science with Python while it does require foundations for statistics for this module, so it appears difficult to understand some mathmetical concepts for beginners. Thus I suggest some more detail explainations/practices for core parts like model development.
Moreover, there are some mistakes/typos in labs, e.g. Week5's Model Evaluation and Refinement, though most of them are minor. Also some libaries are outdated (discovered thourgh warning outcomes), which may need updating.
By Sk. T R•
Apr 03, 2019
It has been a fantastic experience to have gone through this course materials. Although I found the lecture videos quite quick to the extent that we fail to understand the concept well. But while going through the labs carefully, I was able to get the concepts right. So only because the lab part was well organized, the course was helpful to me. But had it been the lectures alone, then it would have been difficult to grasp all the concepts clearly.
By DI C•
Jul 07, 2018
Great course! More hands on and practice, a bit lack of theories, compared with Andrew Ng's ML course. And there are a few typos or mismatch in the course materials that need more attention. However, I especially like the fact the example, i.e. predicting car price, has been revisit and further developed through the 5-week course. Just finished round 1, guess I need to go over it again (maybe again) to grasp more details. Recommend the course!
By Jianxu S•
Sep 07, 2019
Overall the course is well written. There are a few typos including in the instructions for final assignment. I feel that a summary is missing for the overall data analysis process and methods. This course is the longest in the series so it takes a lot of effort to get through. I did not have much Python background so it was a bit challenging at the beginning but the material was very helpful in bringing me up to speed.
By Matthew S•
Jun 20, 2019
This course was challenging. I will probably want to come back to it after learning a bit more statistics. But it was cool stuff, and at the right level of depth. (The only criticism I have is that there are some problems with the final assignment, a small discrepancy between the question in the notebook and the question on the assignment submission, and some other formatting issues on the submission form.)
By Ekaterina K•
Aug 20, 2019
Very good lectures, but the final project takes way longer to set up than to complete: finding the link to the final assignment and making it work in Watson took me too much time. There should be an option to do it outside Watson environment without loosing points because Watson is very slow. Moreover, the assignment and the link to the dataset should be posted more clearly.
Jan 01, 2020
The material are structured very well. The explanation in the video and lab tutorial really help to understand. The discussion forum is active and the teachers are responsive. You will also get a free certificate and IBM badge. Though there are some typos and errors and some things left unexplained, but overall it's good. Hope you guys can increase the course's performance.
By Jess M•
Feb 28, 2019
Covers a lot of content very quickly with not enough opportunities to practice using and applying the code. Having lots of quizzes is good for testing passive knowledge, but more active hands-on application in labs would be most welcome. Useful content, but I am going to go take an intro to Python course so that I can actually follow and use what is presented here.
By Eugene T B•
Sep 03, 2019
Some of the course skates over pretty difficult information really quick and then gives you challenges that haven't really been that well explained, so some self-research is required. The assignments are also pretty copy/paste + modify a couple of variable names so you have to put in the effort to really get good value out of the course.
By Anuradha B O•
Jul 14, 2018
The course is very interesting and concise, it has a very logical flow. The best parts about the course are quiz embedded in the lectures and detailed lab assignments. However, there are few errors in the lab and assignments, which need to be rectified. Otherwise, it would have been 5star from me. Thank You for desiging this course.
By Ming E L•
Dec 18, 2019
Easy to understand and grasp for a beginner. Good refresher for those who have some basics of programming down. Typos in the reference codes here and there but no major problems. Other than that the Watson interface is alright to work with however there will be some lagging some times. I enjoyed the process of learning this course.
By Joseph O•
Mar 11, 2019
a few discrepancies here and there, please see the comments in the discussions. Other than that, very good! This course was more difficult than the others, and so i guess this is why employers prefer potential employees hold a PhD, or at least maintain a high algebraic/calculus/statistical aptitude
By Sumit C•
Jun 06, 2019
The underlying basics of Data Analysis with Python were deeply conveyed. Simple examples and easy to operate commands were greatly described. I would suggest everyone take this course whether or not they know to code. It is always great fun to learn new concepts and Coursera makes it possible.
By John B•
Sep 09, 2019
Contained some simple grammatical errors, as well as some syntax typos in some of the modules. The most relevant thing I would criticize is the lack of depth with describing certain topics ion the modules as they can be very complex. I recommend studying the section notebooks thoroughly.
By Michael K•
Apr 28, 2019
There is a lot to unpack in this course. If you have a statistics background, this may seem kind of trivial, but for the rest of us it is loaded with ways to view data. My only criticism would be that it sometimes skims across an advanced topic without really giving a general overview.
By Irving B•
Oct 11, 2018
This course gives a very clear view of the tools used to find the best way to analyze data when looking for the best model to predict target values. The use of Jupyter Notebooks to run code for the data analysis is very useful and enables the student to experiment on his own for options.
Mar 24, 2019
I have start this course without knowing any Python code. I made it through but with a lot of rock with all the code. like a For loop or simple Python code. I suggest to study basic Python code then start this course but this course did push me a lot on Python code learning with Youtube
By Lauren J•
May 07, 2019
This was a good course, but didn't have as much labwork as I would have liked. There were a lot of labs, but they were mostly already completed by the instructors - more of a read-along than actually doing work yourself. That said, it was a valuable course and don't regret taking it.
By Benjamin S•
Jan 17, 2020
The course teaches an incredible amount of information in a relatively short time. The downside to this is that users don't get enough practice within the course on the data analysis methods and functions taught. Additionally, there are a lot of typos that need to be fixed.
By Mukul B•
Nov 09, 2018
This module is loaded with concepts. Even though they are introduced in a logical sequence, it gets a little overbearing and tend to lose the relevance in the context of car price prediction. At least, now I am aware of the techniques, methods and python's capability.
By Luis O L E F•
Nov 14, 2019
Good introductory course. Even though it is an introduction, the course would benefit a lot from including a bit more of theory, even as optional material. For example, including theory about ridge regression, instead of just mentioning how to implement it in Python.
By Juan V P•
Apr 16, 2019
I think that you missed more detailed explanations on how to analyze the results, especially for those of us who are not mathematicians or with advanced knowledge of statistics. But, is a fact that In the end it was the course i've enjoyed the most. This is awesome
By Vera C•
Sep 11, 2019
The course is quite challenging for me as a beginner of using python to perform linear/non-linear model development. It is good in terms of the plenty of content for people to learn but it is quite hard also as it would be better to have more practice / examples.
By Anton V•
Jan 15, 2019
I think this is a decent course that introduces data analysis on a basic level. The first 3 weeks were really well written, the last 2 weeks have some faults in them though, like values referred in the text which does not match with values written in the code
By avish j•
Dec 15, 2019
Good to start with, this course provide you with the step involved in Data analytics but no logic behind these steps are provided. If you are new to python library this course will be helpful for you as it involve use of pandas, Scikit, Scipy and matplotlib.