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Learner Reviews & Feedback for Data Analysis with Python by IBM Skills Network

16,337 ratings

About the Course

Analyzing data with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the basics of data analysis with Python to building and evaluating data models. Topics covered include: - collecting and importing data - cleaning, preparing & formatting data - data frame manipulation - summarizing data - building machine learning regression models - model refinement - creating data pipelines You will learn how to import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations. You will then predict future trends from data by developing linear, multiple, polynomial regression models & pipelines and learn how to evaluate them. In addition to video lectures you will learn and practice using hands-on labs and projects. You will work with several open source Python libraries, including Pandas and Numpy to load, manipulate, analyze, and visualize cool datasets. You will also work with scipy and scikit-learn, to build machine learning models and make predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge....

Top reviews


May 5, 2020

I started this course without any knowledge on Data Analysis with Python, and by the end of the course I was able to understand the basics of Data Analysis, usage of different libraries and functions.


Apr 19, 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.

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1776 - 1800 of 2,480 Reviews for Data Analysis with Python


Nov 24, 2021

First of all I would like to thank all the instructors for creating this course. But I feel the couse content lacks a lot of clarity if someone is taking this course for the first time. The video lectures lacks a lot of the important theoritical and coding concepts. And in the Hands-On lab there were many coding sections again if someone is doing this course for the first time it will be very hard for them to understand. In my opinion the the video lectures should have been a bit more lengthier with more explanation of the coding part as why some coding sections or some lines of codes were added and also a bit more theoretical explanations.

By Nguyen D H A

Aug 3, 2019

A good starting point.

Some of the concepts could have been explained more clearly, I have decent mathematics understanding and sometimes still felt like I was hopping from this to that (regarding the codes). I understand that they're trying to teach many things in basic level, but total video time was about only 1 hour for the whole course... I wouldn't mind watching a little more or getting additional reading materials to get the context & familiarize myself with the codes (I do additional practices on my own so that's fine, but directed-study is always nice, and easier)

The labs were really helpful though, so I'd say go for it!

By Muhammad S H

Mar 17, 2020

I think the course was good, but the complexity level of the labs was a bit high. I mean, the leap in skill level required could have been made more easier. There are many new functions utilized in the labs that we have not been made familiar with. So, a lot of documentation-perusal and sifting of other online resources was required, especially with the Polynomials and Ridge Regression, the last Lab. I think the contents of the last Lab (Model Evaluation & Refinement) should be elaborated on and explained with greater clarity, introducing new functions and code-parts along the way.

By Arnold W E

Feb 22, 2020

One of the few good courses I have had. I learned a lot, used much of it in the labs. The lab for Week 5 was very confusing, as was the final one. The other labs were great, but Week 5 and the final were very disjointed and uneven. There were several things I had hoped they would put in the lab, but there was no first-to-last example lab, which is what I wanted. Without actual instructors (as in live training) this should be expected, and if I had paid for this I would be upset. Problems 7-10 on week 5 are garbage!

Still, one of the best on Coursera, from my limited point of view.

By Uchi

Aug 19, 2020

The course is great but they don't really give enough information about some stuff, I hoped they would explain what is really the goal of alot of snipets of code and which part does what in a deeper level instead of just scratching the surface,

i had to teach myself somestuff and it was a little challenging for a while specially that i don't have statistics background i, Iam not talking about more content i mean more info more details in other words what's obvious for the developers who provided this course isn't that obvious for new learners

By Imtiaj A C ,

Apr 18, 2020

Of course I've learnt a great deal about data analysis using python in this course. The course videos were made in a way that even the most difficult topics could one learn very easily. And after-module-labs were great to test the topics learnt.

One thing that stopped me from giving full 5-star was the final assignment. It was way too simple in my opinion. Most of the discussed topics weren't even there. I guess it would be much better to make the final assignment a little bit more thorough and to some extent, more difficult.

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 Jonathan K

Mar 8, 2020

Good because provided breadth - teaching lots of different data analytics tools. The cons were that it didn't actually force you to code until the final product, and it also tried to do way too much in one course. I wish it just went more in depth into beginner topics like cross-tabs and linear regression, as opposed to trying to cover introductory stuff as well as beginning machine learning in one course - which caused the course to sacrifice depth - a deep understanding of any given topic.

By ira d G

Jun 4, 2020

I love this course! I think it's well organized. And they made sure you really learn in the lab. I'm very hands-on when it comes to embedding important skills (via the lab exercises). I do wish they would associate the terms with, say, statistics or machine-learning, so I would delve into more research -- even more than necessary. Not everyone who wants to learn Python is already well-versed with the prerequisites. But overall, the course is thorough enough and well-articulated.

By Juan M L F

Jan 23, 2020

This course is good if you already have some experience in Python and its structures, or if you have some knowledge in programming. You will learn some basic data manipulation and exploration techniques and also start with some of the model evaluation metrics in order to assess the (regression) models created. Overall good experience. If you already have some knowledge of Python SciKit Learn and Pandas, you could easily cram this course in 2 days (all-in) without too much sweat.


Apr 3, 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 6, 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 James S

Sep 7, 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 Francisco M

Apr 5, 2020

The course is good but sometimes the exercise texts are not very clear and some of the lessons are very straightforward, leaving many doubts. The course should have a larger series of exercises and an automatic correction system that facilitates the review of the exercises. In addition, it would be interesting to have a module on how to use IBMDB2 without the online platform, but through Jupyter on the computer.

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 Veena W

Nov 8, 2020

It's a great course for beginners. A lot of topics are squeezed under this course. But, I wish the topics were a bit more elaborated and the number of videos increased. To back up the topics related to any calculations, actual algebra and statistics implementation should have been shown. Because of the confusions, tons of questions were arising during lab activity. Quizzes and lab activities were good.


May 30, 2020

Although this course comprises the most common techniques used for Data wrangling and basic modeling, it does not go any deeper into understanding the logic behind many of the subjects.

Perhaps, giving out some aditional lectures for every week lessons could be of good help to better understand this topics, so the learning process would not be just a "follow through" that just works for ideal scenarios.


Apr 26, 2020

The final project left out some higher cross-validation methods like Grid search and model comparison. Nevertheless, the course tried to cover a lot of useful and relevant examples of the whole process, as well as providing good practice opportunities. Personally, I would love to have more practice on each module so that I can turn the knowledge into my own. Overall, a well-designed course!

By Teh C Y

Aug 10, 2021

Week 1 until Week 4 the syllabus are okay & understandable, but when it reached week 5 it's another level, like suddenly jump from beginner level to advance level without detailed explanation. I have to ask people or search online to look for answer & further details to understand the whole concept. This reminds me of the movie series GOT... exciting beginning but terrible ending

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.

By Celine

Jan 1, 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 Venkata P U

Jul 25, 2020

This Course is extremely useful for quick learning of skills. This course takes you into world of data analytics at the same time giving you practical experience, unlike many other courses. All the topics in this course are up to the point and tell you its application rather boring you with details. If you are a beginner then this is a perfect course to begin with.

By Mouafo D

Jan 20, 2020

Well design for beginners with a scientific profile. The course starts moderately and covers a large amount of concepts. I advise to take notes and often to deepen certain concepts in dedicated tutorials on google or YouTube and other appropriate platforms. Cleaning mistakes on the slides and the notebooks will be great and make the learning experience more fluent.

By Jess M

Feb 27, 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 Sanjay R

Apr 3, 2020

The course videos were excellent! The final project did a good job in covering the course material. However, the support to the course was unacceptable. I never got a response to any of my questions after posting them twice and waiting for a day. I then just decided to submit my project without waiting for a response since I felt my wait will be in vain.