19 de abr. de 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.
5 de may. de 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.
por Gerson C H•
5 de feb. de 2020
Its a great introduction a clear explanation about Machine Learning, generation of linear regression models and all the things to do before to the analysis front the data. I'm very excited and gratefullnes.
por Victor A d S•
13 de jun. de 2022
Even though I know a little about pandas, with this course I was surprised and I was able to learn even more, besides, the examples of statistical tests that are essential in data analysis are very useful.
por Magesh J•
27 de may. de 2021
A fast and quick way to get into the data science using Python. The program includes well defined Jupyter notebooks which can be printed out and used a reference. The videos are short and well presented.
por Daniel K•
25 de oct. de 2019
Grate course. Really straight forward. I live the design of this course (a lot of quizzes to harden knowledge). I couldn't find any code for box plot during course and I had to make one during assignment.
por Nima G M•
4 de oct. de 2020
One of the greatest courses to become familiar with different Python libraries for machine learning, more specifically, the Pandas library, in which we should have the ability to work with "dataframes".
por Souparna C•
7 de ene. de 2021
I'm really over-whelmed!...And I mean it. After completing this course one can get a clear insight of data. All topics are clearly explained. All lectures and labs are well structured. Thanks Team IBM!
por Saravanan S•
2 de jul. de 2020
This course is very good and it covers all the fundamental concepts used by pandas and numpy. It covers the linear regression, ridge search, grid search, polynomial regression and Pipeline construction
por Dominique D•
6 de abr. de 2020
It gives a very good introduction on most of the basic statistical methods. It is a bit challenging to absorb it all, but all by all very doable. I enjoyed this one and learned a lot from it! Thank you
por Carol L•
22 de abr. de 2020
Me gustó aprender procesos de análisis de datos, algunos un poco complejos de entender pero se saca el tema. Seria bueno colocar algunas referencias para ir mas en detalle en algunos puntos complejos.
por Vallian S•
31 de ene. de 2022
This is totally one of the hardest course I've ever taken on Coursera. It's packed with knowledge I did not know before. Definitely recommended for people who want to learn data analysis with Python.
por Md. A A•
1 de dic. de 2020
A compact course. Good one who want to learn within a short period of time. But if one wants to understand the topics well, then he/she should go through the documentation of respective libraries.
por Carlos D•
15 de abr. de 2020
Great Introduction to Data Analysis, the concepts going from the basic to deep in data-testing and data-training, as well as several applications linear and polynomial regression to data analyze.
por Adegbuyi M A•
9 de dic. de 2021
Most of what you'll learn in this package are fundamentals to other knowledge areas. So, practice both in and out of the course.
I appreciate the coordinators in making it possible. Thank you.
por Brian k•
9 de may. de 2021
I love the practicality of this course. It's not just learning theories but you actually follow along. You only need a good computer and you learn serious staff taught in the best way possible.
por sapna y•
23 de may. de 2020
Data analysis with python has a high standard of content.I hope this is useful for me to crack DS interviews.The content is well structured.Quizzes,assignment and video lectures are corelated.
por Wolf Z•
8 de nov. de 2020
A great introduction to fitting data in python.
The core principles and measures are well explained.
The only slight minus point: No information about the interpretation of fitting parameters.
por ALFIYA K•
14 de jun. de 2019
Enthralling and motivating course! Lectures and practices are conveniently balanced! Labs are so excited and realistic! Many thanks to all creators and teachers for such kind of awesome job!
por Hao H•
10 de sep. de 2020
Well arranged course that covers the essentials statistics with Python. But be aware this is an elementary course that may be a little too easy for those who have experiences in statistics.
por Juan E F A•
15 de feb. de 2020
It was an excellent way to begin in the path of data science. I really enjoyed all the knowledge they shared. I'd lie if I say that it was a piece of cake, but it wasn´t impossible, either.
por Narasimhan, S•
25 de may. de 2020
This was a good course to understand some of the analysis concepts that are available.I would rate this course for anyone who wishes to have a good foundation of Data Analysis with Python.
por Dr. J N•
17 de abr. de 2020
This course precisely and comprehensively covers important aspects of Data Analysis with Python. I strongly recommend this course for those who are serious about Data Science using python.
por carolinne r•
24 de sep. de 2019
Excellent course, it helped me a lot to get started with Python. Still today I always consult my personal notes on this course to perform data analysis in all types of projects I work on.
por Jayesh M•
24 de ene. de 2020
I like this course more than anything. As this course give me many useful insight of model as well as this included the many things like from model fitting/training to improve the model.
por John S S D•
12 de jun. de 2020
The course is very hands-on focused and that's great. Nevertheless, if there were some documents that summarize the week content (attibutes or codes characteristics) would be fantastic.
por Harsh V J•
25 de abr. de 2020
It is a good course on Data Analysis for both predictive and descriptive analysis. I think there should be more practice assignments for more hands on experience on predictive analysis.