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 mai 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 Miranda C•
23 de jul de 2020
This course went fairly well, I just hope that the information will be repeated in the next course in the certificate program (IBM Data Science certificate) as I don't feel like the information has really sunk in . . .
por Ankit S C•
15 de jan de 2020
The Model Training and Evaluation weeks could have been more elaborate. Instead of just telling to do something, it would've been better to explain why we are doing it and how is it working internally, at a high level.
por Mario A T•
28 de fev de 2020
Tuve problemas con crear la cuenta en IBM cloud con mi correo personal primario , no pude encontrar soporte ni orientación de que hacer , me toco ingresar con otro correo , no se porque no fue posible con el mio
por Junior N•
18 de ago de 2019
This course is pretty good and give a good introduction to data analysis with python. However, there is a problem in the course's methodology : functions are given without any introduction...just implementations.
por Glison M•
9 de ago de 2020
The course was good in introducing Pandas, Numpy and Sci-kit to beginners. Adding more graded programming activities would be a great addition to this course, as there is only one graded programming assignment.
por Orsolya N•
26 de jun de 2020
Certain parts were too fast, and there were some technical issues with the labs at times, but there's always the possibility to look up the blurry parts online. Overall it was interesting and well put together.
por Kyle H•
25 de fev de 2020
This definitely could be more project based than it was, and focus more on applying coding skills than just reading them and watching videos about them, but it's a great overview of some useful techniques.
por Keerthi S•
3 de nov de 2019
The final assignment had some errors in submission with some questions not allowing for upload of the answers (Question 3, i.e.). Did not feel great about this error. Otherwise, great course - very useful.
por Mantra B•
3 de nov de 2019
Overall a great course. All essential Data Analysis processes are covered in this course. A small nitpick is that Week 5 material was a little less in depth. Moore examples in videos will be a great help!
por Christian A S•
2 de jun de 2021
Los procesos de practica asumen que el manejo estadístico, es solo dar el resultado, pero creo que el contenido es bastante profundo y la practica debe ser mas concentrada en evaluar diversos escenarios.
por Saptashwa B•
18 de jan de 2019
Great course for introductory data analysis with Python. Very good for fundamental understanding of overfitting, underfitting, precision, accuracy and using grid search method to optimize fit parameters.
por Harshit R•
8 de ago de 2020
Some Statistical terms and concepts were covered quite briefly due to which some amateur student has to refer additional contents like Youtube. Same with me. Quizes can be made tougher to raise the bar.
por Chuxuan Z•
3 de abr de 2022
pros:very easy to understand, even the statistics knowledge
cons: incomplete python sentences in the video require extra efforts to undertand, such as no previous sentenses for an object (i.e. x_data)
por Sule C•
12 de ago de 2020
Thank you very much to the instructors. I liked the course but it could have been better designed. More exercises ascending from easy to hard & real and teaching quiz questions would make it perfect.
por Roberto M•
10 de jun de 2020
Great course to learn the basics for Data Analytics using Python.
I really liked the framework and data analysis template or process given in the labs. I will use them as a reference for my real job!
por Brijesh D•
23 de nov de 2019
Really interesting course, if one wants learn programming language. Well designed and structured. Only suggestion is, if the small videos contains example that be really great to understand it well
por Luis M•
10 de mar de 2020
Very good course that goes straight to the main topics needed to work on data analysis using Python. This will kick start my learning process which will be followed with a lot of coding practices.
por Cassie T•
14 de mai de 2021
Good course, sometimes moves a bit fast in the final modules and the labs are quite tough but great course and would recommend to broaden your knowledge of coding, data analysis and visualisation
por Bharat M•
16 de jul de 2020
Although good to learn the know-how of basic data analysis techniques, the quizzes are predictable and you don't end up coding as much as you should.
A good starter course to wet your feet in DA!
7 de abr de 2020
Very clear and easy to learn. The lab helps a lot, it gives me an intuitive instruction of the class. But some of the points seem too shallow, hope the course could provide some deep knowledge.
por Mark W•
12 de nov de 2021
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.
por Nikhil D•
31 de jul de 2021
Totally overwhelmed with the course contents and easyness in teaching. The course will make you familiarize the fundamentals in a way that you will never forget when you used in a real world.
por rahi j•
17 de out de 2018
It will be helpful if a video is added on:
1) how to store multiple results from different models in single dataframe
2) how to automate the process. More example needed on Grid and Pipeline.
por Rodrigo D•
24 de fev de 2019
Great course, you can understand in a general way the use os Python to analyse raw data and organice it to create a better model. However I couldn't use in a proper way the external tool.
por Mason C•
28 de abr de 2020
Theory and examples are good. Suggest having full and complete Python course code with more examples of each coding. So we can get more ideas and understanding of the Python environment.