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Voltar para Data Visualization with Python

Comentários e feedback de alunos de Data Visualization with Python da instituição IBM Skills Network

4.5
estrelas
10,688 classificações

Sobre o curso

One of the most important skills of successful data scientists and data analysts is the ability to tell a compelling story by visualizing data and findings in an approachable and stimulating way. In this course you will learn many ways to effectively visualize both small and large-scale data. You will be able to take data that at first glance has little meaning and present that data in a form that conveys insights. This course will teach you to work with many Data Visualization tools and techniques. You will learn to create various types of basic and advanced graphs and charts like: Waffle Charts, Area Plots, Histograms, Bar Charts, Pie Charts, Scatter Plots, Word Clouds, Choropleth Maps, and many more! You will also create interactive dashboards that allow even those without any Data Science experience to better understand data, and make more effective and informed decisions. You will learn hands-on by completing numerous labs and a final project to practice and apply the many aspects and techniques of Data Visualization using Jupyter Notebooks and a Cloud-based IDE. You will use several data visualization libraries in Python, including Matplotlib, Seaborn, Folium, Plotly & Dash....

Melhores avaliações

LS

27 de nov de 2018

The course with the IBM Lab is a very good way to learn and practice. The tools we've learned in this module can supply a good material to enrich all data work that need to be presented in a nice way.

AM

13 de ago de 2020

Great course, one of the best course to get hands-on learning for Data Visualization with Python. Particularly the lap exercise, it will make you think on every line of code you write. Excellent!!!

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1201 — 1225 de 1,629 Avaliações para o Data Visualization with Python

por Kang R K

5 de nov de 2019

short course but learn useful python package Folium efficiently

por Sai Y

23 de jan de 2023

Overall Best Course to learn . Needed in more indepth concepts

por Mohit S C

10 de mar de 2022

This course is so much benifical for me to visualize the data.

por William O

28 de abr de 2020

Thanks for the content of this course. I really learned a lot.

por Nicolás G S I

31 de jul de 2019

The final assignment is not too clear.Question 2 specifically.

por Serdar M

25 de nov de 2018

more explanation on functions' and methods' parameters needed

por Frank H

6 de fev de 2020

Some new packages i've never seen. Map one was really cool.

por Hong W

13 de mai de 2020

Good course to learn basic knowledge of data visualization

por Kevin D

26 de set de 2019

first of the courses where things weren't spoonfed to you.

por Greg G

6 de jul de 2019

An interesting course with a number of practical examples

por Nath S

15 de abr de 2022

Really helped me to understand diferent types of graphs.

por Ahmad S

30 de jul de 2020

Very good course but need more examples and explanations

por Aloke D G

24 de set de 2019

Good insights into various plotting methods and library.

por Ankit K S

13 de fev de 2020

Very wisely chosen content of ungraded lab assignments

por Murat A

27 de set de 2021

I had to retake the quizes which I completed already.

por Mirjan A S

22 de ago de 2020

Very Good Course for Data Visualization with Python..

por Gaurav J

3 de mai de 2020

Will be good if seaborn is also included in syllabus

por Ravindra D

18 de nov de 2019

Brief introduction to Data visualisation using Python

por krantiveer s

8 de abr de 2019

great course content but it should be more disciptive

por Vivek P

10 de jun de 2020

The course was good, but some documents were missing

por Satya V P C

17 de jul de 2019

Very nice course with all explanations and examples.

por Yohanna H

14 de abr de 2021

Some of the code they give you to update is buggy.

por Yang D

15 de fev de 2019

All the course is good except the final assignment

por Ishani S

25 de abr de 2020

The course was thorough in data analysis content.

por Hunter I

17 de abr de 2020

Liked it a lot, a little rushed but learned a bit