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Comentários e feedback de alunos de Análise de dados com Python da instituição IBM Skills Network

4.7
estrelas
16,210 classificações

Sobre o curso

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....

Melhores avaliações

RP

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.

SC

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.

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1851 — 1875 de 2,449 Avaliações para o Análise de dados com Python

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!

por wangqiucheng

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.

por NAPA S M

7 de mai de 2019

Questions while listening to lessons in some of the lectures are coming before theory explained by the teacher .Better if question is at least 10 seconds after related theory explained.

por Cristian A M L

17 de fev de 2020

Los temas tratados son muy útiles y se desarrollan de gran manera. El herramienta de LAB es la más completa del curso. Considero que se puede aumentar la rigurosidad de la evaluación

por Daniel A

31 de mai de 2019

This was pretty good, I think maybe the best in the IBM machine learning certificate. I took Andrew Ng's course prior to this, so to watch python sklearn in action was a real treat.

por SHALINI G

1 de out de 2018

It is a good course for beginners but I feel that the quizzes could have been a bit more challenging. And if the codes were executed in the Python domain , it would have been nice.

por Charles R

9 de jan de 2021

Everything felt just a little too easy. I have minimal Python skills and nearly failed college statistics, but I never had any trouble here. The exercise notebooks were fantastic!

por mitul p

9 de nov de 2019

Very interactive and informative content.Covered all the data analysis related concept. I would suggest that spare some more time on Regression techniques to details information.

por Amanda S

3 de ago de 2020

I thought this course was very informative, but there were some typos and I thought some of the concepts were introduced too quickly without links to previous or upcoming ideas.

por Ravi K

8 de dez de 2018

Good content through out the learning, the lab notebooks are great resource to do the Hands on by ourselves. Includes each corner of the analysis methods. Good foundation course

por Rakshith R

28 de jun de 2020

This is a very useful and very appropriate to those who want to pursue their career in Data Science.

Me as an data science enthusiast liked the course, and would also recommend.

por Sam T

10 de jun de 2019

Course provides a good intro and the visuals are great. It doesn't however go deep into each topic and doesn't provide enough examples to explain concepts for different cases.

por RAM K B

5 de jun de 2020

There were some statistical concepts in Week 4 and Week 5 which were difficult to grasp for a beginner like me.

More in depth explanations were required which were missing.

por Lim Y T

23 de abr de 2020

Great course. especially on the final assignment and as a new learner without any basic knowledge on python skill. it took me quite a while and challenge to get it complete.

por Aaron Z

12 de jun de 2020

Would be a bit hard for someone who hasn't got a background with math and statistics knowledge. Not very much explanation. Also, not much interpreting for the methods used.

por Mark H

10 de fev de 2019

Pretty dry material. Hard topic to teach since the process really comes from experience. Could stand to focus a bit more on ways to explore and clean data. Not bad though.

por Setiadi S

21 de jul de 2020

The lab is good for learning, the quiz i think should be add more questions, too small, overall is ok for the beginner for learning the data analysis with Python, thanks.

por Or R

4 de ago de 2020

Good introduction to the things one can do with Python and Pandas, but overall fairly basic and does not require the students to actually program something of their own.

por Andrew B

25 de jan de 2019

Good for a first course in data analysis however this course covers the subject on a very superficial level. There are a few errors in the assignment's solution guide.

por Rahul S

10 de abr de 2019

Good but in the end of the course specially week 4 and week 5, speed of information providing in videos get to very high speed comparative to other weeks information.