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.
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.
por Roberto B•
I'm not convinced that this is a great way to learn, I just feel there needs to be a better way of learning this than the approach this course takes, I kind of learned the python commands but I'm not sure I understand how to apply them in the real world. We'll see
por Toan L T•
Decent videos on Data Analysis techniques.
But the labs are poorly constructed: typos, inconstant question and solution, un-commented code and under-explained lab result.
It's a shame since the labs in other courses in this series are very high-quality.
por Raj K•
It would be great course for beginner to have idea about different steps involve in data science job. I would recommend to go with this course. I just took 3 days to complete this course and you can do in 2 days also. Depending on your speed.
por Damian D•
There are some mistakes in the course (wrong transcryptions, missing cells in LAB).
The material is quite difficult and more explanation / exercises would be needed.
There is no assignment at the end of the course which I consider as minus.
por Filipe S M G•
Good introductory course on Data Analysus with Python. Since the course is short, the functions and concepts are explained very quickly. There are also many mistakes in the slides, notebooks and even in the final assignment.
por Benoit P D•
The content of the course is very interesting. There are lots of typos in the lab workbooks though. Additionally, i found having to use Watson Studio for the assignment / labs as opposed to plain Jupyter a little annoying.
por Sadanand U•
It would be great if we go in a little more details of when to use which metrics for evaluation. Instead of running through a bunch of concepts you could have spent a little more time in each of them.
por Joseph M•
There were serious problems with this course, not in the instructional material but in the execution. There were multiple typos in the code. The especially grievous ones being in the dictionary names.
por Deren T•
This is the 6th course of the specialization and I gave 5 stars to the previous courses. But this course have many typos in videos and codes. It makes harder to understand some points.
por Kristen P•
The work in this course was incredibly interesting. However, there are many errors and the forums went for over a week without response to questions...It seems hastily put together.
por L V P K M•
Videos are very fast and dont go into details. Assignment is very easy, it could have been more challenging which can test and make learner to think using several concepts learned.
por Ivan L•
Typos are very unprofessional and spoil impressions of the course. Tests and labs are super-easy and do not make you think, and you only need to repeat commands from the lectures.
por Vladimir K•
So many errors in materials. It's unacceptable for course of such level. Even though people mentioned these errors in discussion forumns noone seems to bother about correct em.
por Naveen B•
Some of the codes shown in the videos had minor errors. Also, a bit more explanation for function (in statistics terms) would have helped in having a better understanding.
por Marta I•
This is a good course for beginners with Python. The content is explained in a very direct and comprehensible way, but more programming exercises and tasks are required.
por Ying W O•
There are lots of typos in the labs and assignments, which can be frustrating. I expect better quality from IBM. Content is great and easy to understand nevertheless.
por Matteo T•
This course is quite good. The bad thing is that the arguments of the last "lesson week" are treated very superficially, taking for granted some advanced knowledge.
por Marcel V•
A lot (too much maybe) is covered in this coarse
It really helps a lot when you know some statistics. Like linear regression,
Why gridsearch was covered I wonder.
por Dylan H•
While a bit fast and loose with the concepts, does contain a lot of practical code as to how exactly to bring things discussed about, which is appreciated.
por Xuecong L•
Thanks for teaching me the systematic way to do data analysis! However, I found quite a few mistakes in the lectures in this course, hope it will improve!
por Hao Z•
IBM Cloud is difficult to use.
The generated link of notebook will not share the latest version, if you click the share icon before editing the notebook.
por Neo B•
Data visualization was taught in details in course 7 and regression was taught in course 8. With no backgrounds, the codes in this course are scaring pe
por Goh S T•
The section on model development and evaluation is not so clear. It is difficult to understand if you have no prior knowledge of machine learning.
por Girgis F•
Course was great however i felt a lot of material was covered in a short period of time, this course can be 2 or 3 courses based on the content
por Guillermo M M•
It is missing a last project like in the two other courses... It would have been quite fun to be able to apply what we learnt in a project.