EH
It is a very valuable course that I have learned for the Python skillset. It contains some advanced methods. It helps me to build more confidence in using Python and understand the concept in general.

This action-packed Specialization is for data science enthusiasts who want to acquire practical skills for real world data problems. If you’re interested in pursuing a career in data science, and already have foundational skills or have completed the Introduction to Data Science Specialization, this program is for you! This 4-course Specialization will give you the tools you need to analyze data and make data driven business decisions leveraging computer science and statistical analysis. You will learn Python–no prior programming knowledge necessary–and discover methods of data analysis and data visualization. You’ll utilize tools used by real data scientists like Numpy and Pandas, practice predictive modeling and model selection, and learn how to tell a compelling story with data to drive decision making. Through guided lectures, labs, and projects in the IBM Cloud, you’ll get hands-on experience tackling interesting data problems from start to finish. Take this Specialization to solidify your Python and data science skills before diving deeper into big data, AI, and deep learning. In addition to earning a Specialization completion certificate from Coursera, you’ll also receive a digital badge from IBM. This Specialization can also be applied toward the IBM Data Science Professional Certificate. This program is ACE® recommended—when you complete, you can earn up to 12 college credits.

EH
It is a very valuable course that I have learned for the Python skillset. It contains some advanced methods. It helps me to build more confidence in using Python and understand the concept in general.
TM
The assignment is quite easy, you just need to understand the code and rewrite the code to finish the final assignmentThis is a very useful course to help us imagin basically what a DS do
MW
Good Course. Very good overview of Python libs -Pandas, Numpy, Matplotlib, Scipy, Scikitlearn and Seaborn. I really enjoyed learning about them and seeing the usage. Highly recommended course.
AA
This course was really interesting and it was great learning experience.A big thanks to a instructor.I got to know new things like folium library (most interesting library of python according to me)
RS
Very in-depth and rewarding project - would be a little better if more specific guidance on what to exactly include in the notebook would be better. But overall very stimulating. Thanks!
TM
it becomes easier wand clearer when one gets to complete the assignments as to how to utilize what has been learned. Practical work is a great way to learn, which was a fundamental part of the course.
CH
I enjoyed this class. It has less lecture and more figuring things out. It was not in my original certificate program, and I decided to go upgrade and pick it up. Glad I did.
RP
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.
TR
The Course Was Good. It would have been better if some lab sections were covered in labs. As we all know understanding a code then reading might help the students grasp better faster and deeper.
JS
Lots of outdated content and not many resources to help, however a lot of it was at least a little bit useful. Though a lot could be cut if you already know a thing or 2 about programming
PK
it was an awesome course to start your journey in data science. Fundamentals concepts are covered in a lucid way. Nicely designed lab work. Some more hands on will help to get a better coding skills.
ZA
Overall it's a good hands on python programming for web-scrapping. The project could have been more challenging but it is not. I hope the future versions of the project is more challenging.
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Course focuses more on forcing you to sign up for various IBM cloud tools than learning python. The final assignment has a 300+ reply thread in the discussion forum because you are graded on the ability to integrate your IBM Watson Notebook with IBM cloud storage, but the instructions have multiple errors, such as not working if you provision your storage in the wrong region.
This class is a shameless excuse for making you sign up for products you don't want, and then grading you on your ability to use them, not your ability to write python code.
Still I don't understand the relation of the course' content and the final assignment.
In addition, I would like to see how should have been done the final assignment, i.e an example corrected and done correctly.
this is the 4th course and still I can't understand anything of python. I haven't learn anything... my money is going to the waste.
IBM says that you don't need previous knowledge of python or programming...that is a lie. I am biochemist and I have a MSc in One health, and during mi years we had lessons of R and R deducer. During that lessons, the materials given by the professors were clear and easy to follow. But this course has been awful..... I am feel like if I were an idiot but I know for sure that I am not. The problem is this rubbish course.
The worst course I took. I couldn't believe the course is provided by IBM. The slide is completely unclear and there are some small mistakes in that. And the final project is aimless, I don't know why you come up with such a project for the beginner. Anyway, I'm so disappointed with IBM and this course.
It is amazing how bad this is considering that it is marketed as an IBM product. This is not the level of quality people expect when they hear the name IBM! You'd be better off paying 9.99 for a Udemy course than taking this course. It is not in depth at all and does a stunningly poor job at building real understanding and competency. The videos and labs are full of sloppiness and errors... again, not living up to the IBM name. I don't know about y'all, but I'm probably never going to pay money for a coursera course again... not really worth it.
I had a lot of problems with the Peer Assignment, which had nothing to do with Python Programming. The Watson environment has changed a lot compared to the learning materials.
I should not recommend this Specialization, because of the difficulties with the Watson environment. I am willing to help solving the problems.
Every course has offered something interesting, challenging, and surprising. I am glad I have spent the time with this class. I would strongly recommend it to others with an interest in data science.
As in the other parts of the certificate, the tasks are simply too easy. The content in the videos (many typos!!!!) are really valuable but the tasks man... Only the surface of the surface will be discussed, no deeping down into the wild. In this course the libraries numpy and pandas are presented but in the final assignment we actually don't needed the libs... When I read the description of the final assignment, I was excited because I assumed we will need to code EVERYTHING ourselves. So really do the thinking of how to solve the requirements, testing it in a notebook out, reading the docs, discovering new cool stuff... But unfortunately my dream did not come true. The most exciting function was already provided and some of the answers were little bit of copy and paste instead of really recalling newly learned knowledge. Before this review I really wanted to give 4 out of 5 stars but after writing this review I will now give only 2 stars. Actually, 2 stars are in my opinion unfair, since the creators have put a lot of time and love in the course content. Unfortunately, so much potential is thrown away
(5 stars): Course was great!!
but,
(0 stars): Instructions for IBM Watson and how to setup the assignments are outdated/incorrect. It took me less time to finish the course, and a lot more time just to figure out how to setup Watson based on the instructions (website & course material do not match). This is something that IBM can greatly improve without a lot of effort, imho.
The final assignment was an exercise in Watson, and barely on the course material :-(
The course content is good. However, the instructions for the final peer graded assignment are unclear. It appears to me that we were graded on our ability to interact with IBM cloud and Watson service not so much python skills also. Although I completed, I would not recommend to other until changes are made. It seems I'm not the only one that is unhappy or who had difficulties, just look at the week 5 discussion forum!
it becomes easier wand clearer when one gets to complete the assignments as to how to utilize what has been learned. Practical work is a great way to learn, which was a fundamental part of the course.
This class was supposed to be for beginners and most of the information in the videos was easy to digest, however, the final project had elements and questions that were never covered. Also, there were many, many spelling and context errors in the videos and quizzes. This lead to a tremendous amount of confusion and I am not happy with this course or my grade. Please consider reviewing the lessons and final project to cater this course more to beginners.
The IBM cloud "service" leaves much to be desired. Multiple times I've experienced outages while I was in the middle of lab assignments. It's a paid course where they give you "free" credits to do the course work in their cloud "service." But the credits are inadequate for the labs and they constantly ask for your credit card to buy more "service." While the class is okay I wouldn't recommend it to anyone because of the poor IBM cloud support.
The syllabus of the course takes you in a roller-coaster ride.
From basic level to advance level and you won't feel any trouble nor hesitate a bit.
It's easy, it's vast, and it's really usefull.
Time waster, doesn't go in depth, the total video content is of less then 2 hours. The quizzes and assignments are too easy.
I recommend Lynda or youtube(derekbanas/thenewboston/CoreySchafer/telusko) or anything but not this course.
Really disappointed.
The final project at week 5 needs to be completely revamped. Poor learning experience...absolutely ridiculous and is creating tremendous frustration amongst all students.
No support from moderators, plenty of typos.
Overall, the course lectures are highly condensed and fly by very quickly. I'm familiar with Python but I still had to go back and review them a few times. Would prefer the video materials to be reviewed more slowly and deliberately.
The final project is a mess. The instructions don't direct to the correct notebook (U.S. GDP data) and that link has to be found from the forums. I could never figure out how to get the JSON credential data of my IBM Watson "bucket", so, my "dashboard" never got generated for my project. After spending several hours on this, as I had scored 100% in the rest of the course, I decided I was going to lose just a few points for this, so, in the interest of time, just moved on.
Need detailed explanation for the topics, course need to be rephrased accordingly.
It was basic Python. You need this to be able to use Python for data science, however the name of the course could have been Python 101.
The programming assignment had errors and it took a long time to figure out (e.g. wrong endpoint was specified). I ended up having to waste a lot of time on this.