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

4.7
stars
16,216 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

RP

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.

SC

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.

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1826 - 1850 of 2,449 Reviews for Data Analysis with Python

By Michael g

Mar 4, 2022

this was one of the better courses in the 10 course package. a bit more focused and less slapped together than the previous courses. also the lab load and have no glittches, aleast for me, unlike other courses. overall good

By Nina D

Oct 6, 2022

Well structured lectures and notebooks worked without issues. I just wished a bit more explanations would have been given in how to interprete the output of some of the results, especially when it came to data predicitions.

By Olatoye D S

May 27, 2022

This is course is a great way of understanding Data Analysis, model training and evaluation, as well as a further indepth understanding of Exploratory Data Analysis, using Python. It was a great time learning through it.

By Enrico G

Apr 9, 2022

Very nice and practical course. It gives you the tools to perform a regression analysis on a dataset. Perhaps, I might have focus a little more on the mathematical theory behind some method, like correlation, p-value...

By Rajan G

Jun 16, 2020

This course helped me a lot in solving my basics about data cleaning, Visualization, Techniques for getting better result and most important how we can judge whether a model is good or not. Thanks for this great course.

By asher b

Nov 12, 2018

this course finally gets to some key Python functions for data analysis. Some of this may be difficult without a basic stats background. Only knock is there are MULTIPLE typos in the slides and labs. Needs to get fixed.

By Miranda C

Jul 23, 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 . . .

By Ankit S C

Jan 15, 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.

By Mario A T

Feb 28, 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

By Junior N

Aug 18, 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.

By Glison M

Aug 9, 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.

By Orsolya N

Jun 26, 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.

By Kyle H

Feb 25, 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.

By Keerthi S

Nov 3, 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.

By Mantra B

Nov 3, 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!

By Christian A S

Jun 2, 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.

By Saptashwa B (

Jan 18, 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.

By Harshit R

Aug 8, 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.

By Lukman A

Oct 28, 2022

A wonderful course that thoroughly explains the basics of data analysis with python, dealing with using pandas to manipulate data. And the notebooks are really helpful and can help with easy revision.

By Chuxuan Z

Apr 3, 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)

By Sule C

Aug 12, 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.

By Roberto M

Jun 10, 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!

By Brijesh D

Nov 23, 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

By Luis M

Mar 10, 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.

By Cassie T

May 14, 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