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Alex Aklson
"Una imagen vale mas que mil palabras". Todos estamos familiarizados con esta expresión. Se aplica especialmente cuando se trata de explicar la información obtenida del análisis de conjuntos de datos cada vez más grandes. La visualización de datos juega un papel esencial en la representación de datos tanto a pequeña como a gran escala.
Una de las habilidades clave de un científico de datos es la capacidad de contar una historia convincente, visualizando datos y hallazgos de una manera accesible y estimulante. Aprender a aprovechar una herramienta de software para visualizar datos también le permitirá extraer información,...
Read more
"Una imagen vale mas que mil palabras". Todos estamos familiarizados con esta expresión. Se aplica especialmente cuando se trata de explicar la información obtenida del análisis de conjuntos de datos cada vez más grandes. La visualización de datos juega un papel esencial en la representación de datos tanto a pequeña como a gran escala.
Una de las habilidades clave de un científico de datos es la capacidad de contar una historia convincente, visualizando datos y hallazgos de una manera accesible y estimulante. Aprender a aprovechar una herramienta de software para visualizar datos también le permitirá extraer información,...
Read more
"Una imagen vale mas que mil palabras". Todos estamos familiarizados con esta expresión. Se aplica especialmente cuando se trata de explicar la información obtenida del análisis de conjuntos de datos cada vez más grandes. La visualización de datos juega un papel esencial en la representación de datos tanto a pequeña como a gran escala.
Una de las habilidades clave de un científico de datos es la capacidad de contar una historia convincente, visualizando datos y hallazgos de una manera accesible y estimulante. Aprender a aprovechar una herramienta de software para visualizar datos también le permitirá extraer información, comprender mejor los datos y tomar decisiones más eficaces.
El objetivo principal de este curso de Visualización de datos con Python es enseñarle cómo tomar datos que a primera vista tienen poco significado y presentarlos en una forma que tenga sentido para las personas. Se han desarrollado varias técnicas para presentar datos visualmente, pero en este curso utilizaremos varias bibliotecas de visualización de datos en Python, a saber, Matplotlib, Seaborn y Folium.
OFERTA POR TIEMPO LIMITADO: La suscripción cuesta solo $ 39 USD por mes para acceder a materiales calificados y un certificado.
Register for this course and see more details by visiting:
OpenCourser.com/course/zytb6q/visualizacion
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Reinforces existing skills and knowledge in data visualization with Python libraries, which are industry standards
Suitable for learners with a background in data analysis and an interest in improving their data visualization skills
Taught by Alex Akslon, who has extensive experience in data visualization
Course content focuses on practical applications, ensuring that learners can immediately apply their knowledge
Utilizes a project-based approach, providing learners with hands-on experience in visualizing data
Optionally, learners can subscribe for $39 per month to access exclusive materials and a certificate
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Reviews summary
Highly recommended python data visualization
This Python course on data visualization is highly recommended by students who gave it overwhelmingly positive reviews. They frequently mention how well the course helps them understand and present data effectively using Python libraries like Matplotlib and Seaborn.
Good for beginners in data visualization.
"Excelente para introducirse al mundo de la Visualización de Datos"
Focuses on Python libraries for data visualization.
"varias bibliotecas de visualización de datos en Python, a saber, Matplotlib, Seaborn"
Course content is well-explained.
"...con tiempo se puede aprender muuuuuucho!"
Lack of instructor support and slow grading.
"no tienes soporte de ningun instructor"
"tuve que pagar un mes mas del curso porque no pudieron calificar a tiempo mi proyecto final casi 20 dias espere!!!!"
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Visualización de Datos con Python with these
activities:
Study graphing techniques
Show steps
Revisiting and practicing this skill before class can help those who may be unfamiliar or in need of a refresher
Browse courses on
Graphing
Show steps
-
Review scatter and bar graphs
-
Explore different graph types and use cases
-
Visualize sample datasets using graphs
-
Practice creating graphs using Python libraries
Review basic Python programming concepts
Show steps
Ensure a solid foundation in Python programming by reviewing basic concepts and syntax.
Browse courses on
Python Programming
Show steps
-
Review online tutorials or documentation on Python basics.
-
Practice writing simple Python programs.
-
Test your understanding by solving coding exercises.
-
Seek help from online forums or mentors if needed.
Review Python fundamentals
Show steps
Prepare for success in this course by reviewing the fundamentals of Python, including data types, variables, and control flow.
Browse courses on
Python
Show steps
-
Review online tutorials or documentation on Python basics.
-
Complete practice exercises or coding challenges to test your understanding.
25 other activities
Expand to see all activities and additional details
Show all 28 activities
Refresh Python programming skills
Show steps
Start the course with a strong foundation in Python programming to increase comprehension and problem-solving skills.
Browse courses on
Python
Show steps
-
Review Python syntax and data structures
-
Practice solving Python coding challenges
Review basic Python syntax and structures
Show steps
Brushing up on basic syntax will make learning more advanced topics easier and quicker
Browse courses on
Python Syntax
Show steps
-
Go over Python tutorials for beginners
-
Complete practice problems and exercises
Organize your course material
Show steps
Gather, review, and organize your notes, assignments, quizzes, and exams.
Show steps
-
Gather all of your course materials.
-
Review all of your materials to get an understanding of all of the topics.
-
Organize your materials in a way makes sense to you.
Participate in online discussion forums
Show steps
Engage with peers and experts in the field by participating in online discussion forums related to data visualization.
Browse courses on
Data Visualization
Show steps
-
Join online discussion forums or groups.
-
Ask questions, share insights, and engage in discussions.
-
Learn from the experiences and perspectives of others.
Practice data visualization with Matplotlib
Show steps
Deepen your understanding of Matplotlib by completing guided tutorials and exercises that cover creating various types of data visualizations.
Browse courses on
Matplotlib
Show steps
-
Follow tutorials on creating basic plots, such as line charts and bar charts.
-
Experiment with different Matplotlib functions to customize the appearance and functionality of your visualizations.
-
Solve coding challenges that require you to create data visualizations from scratch.
Explore Matplotlib tutorials
Show steps
Matplotlib is an essential library for data visualization in Python
Browse courses on
Matplotlib
Show steps
-
Follow along with Matplotlib tutorials
-
Experiment with Matplotlib functions
Follow the Matplotlib documentation
Show steps
Find tutorials and other helpful documentation to guide you through using the Matplotlib library.
Browse courses on
Matplotlib
Show steps
-
Go to the Matplotlib documentation website.
-
Find the tutorial section.
-
Start following the tutorials that are most relevant to the topics you are studying in the course.
Create visualizations from sample data
Show steps
Familiarize yourself with the basics of data visualization by creating visualizations from sample datasets.
Browse courses on
Data Visualization
Show steps
-
Download sample data from the course website.
-
Import the data into a Python notebook.
-
Use Matplotlib or Seaborn to create visualizations of the data.
-
Interpret the visualizations and identify patterns and trends in the data.
Attend a data visualization workshop
Show steps
Gain practical experience and insights from experts by attending a data visualization workshop that covers advanced techniques and best practices.
Browse courses on
Data Visualization
Show steps
-
Research and identify relevant data visualization workshops in your area or online.
-
Register for a workshop that aligns with your learning goals and interests.
-
Actively participate in the workshop, taking notes and asking questions.
Code and analyze data visualizations
Show steps
Coding exercises will increase familiarity with key concepts and reinforce understanding
Show steps
-
Create visualizations using Matplotlib and Seaborn
-
Analyze and interpret data from visualizations
-
Build interactive data visualizations
-
Practice using libraries to customize and format visualizations
Organize and expand course materials
Show steps
Deepen your understanding of course materials by organizing, expanding, and reviewing notes, assignments, quizzes, and exams.
Show steps
-
Gather and organize all course materials.
-
Expand on notes by adding additional explanations and examples.
-
Create summaries of key concepts and formulas.
-
Review materials regularly to reinforce learning.
Collaborate on a data visualization project
Show steps
Working with a peer can result in a deeper, collaborative understanding of concepts
Show steps
-
Find a partner with complementary skills
-
Choose a dataset and define project goals
-
Divide tasks and work on the visualizations
-
Consolidate and present your findings
Practice creating visualizations with Matplotlib
Show steps
Practice is key to mastering data visualization techniques
Browse courses on
Matplotlib
Show steps
-
Recreate visualizations from examples
-
Create visualizations from scratch
Visualize data using different chart types
Show steps
Expand your data visualization skills by creating different types of charts, such as bar charts, line charts, scatterplots, and histograms.
Browse courses on
Data Visualization
Show steps
-
Learn about different chart types and their uses.
-
Choose appropriate chart types for different types of data.
-
Create visualizations using various chart types in Python.
-
Evaluate the effectiveness of different chart types in communicating data.
Develop a data visualization dashboard
Show steps
Apply your visualization skills to create a real-world data visualization dashboard that provides insights and value to an audience.
Browse courses on
Data Visualization
Show steps
-
Identify a business problem or opportunity that can be addressed through data visualization.
-
Gather and clean the necessary data.
-
Design and build a dashboard using appropriate visualization techniques and tools.
-
Deploy and share the dashboard with stakeholders.
Build a data visualization portfolio
Show steps
A collection of visualizations will showcase your skills and solidify your learning
Show steps
-
Create a repository to store your visualizations
-
Visualize data from different sources
-
Write a brief description for each visualization
-
Get feedback from peers or mentors
Explore online tutorials on advanced data visualization techniques
Show steps
Enhance your data visualization skills by exploring online tutorials on advanced techniques, such as interactive visualizations and data storytelling.
Browse courses on
Data Visualization
Show steps
-
Search for online tutorials on advanced data visualization techniques.
-
Follow the tutorials and implement the techniques in your own projects.
-
Experiment with different techniques and explore their capabilities.
-
Share your findings and insights with others.
create data visualizations using the Matplotlib library
Show steps
Reinforce your understanding of data visualization techniques by creating visualizations using the Matplotlib library.
Browse courses on
Data Visualization
Show steps
-
Choose a dataset to visualize.
-
Import the Matplotlib library.
-
Use the Matplotlib library to create a visualization of the dataset.
-
Save your visualization as an image file.
Create a data visualization portfolio
Show steps
Showcase your data visualization skills by creating a portfolio that includes a variety of visualizations you've created using Matplotlib.
Browse courses on
Data Visualization
Show steps
-
Gather a collection of different data sets that represent various types of data.
-
Create visualizations for each data set, using appropriate chart types and techniques.
-
Write brief descriptions for each visualization, explaining the insights it provides.
-
Host your portfolio online or share it with others for feedback.
Build a data visualization portfolio
Show steps
Showcase your data visualization skills by creating a portfolio of visualizations that demonstrate your abilities and understanding of data presentation.
Browse courses on
Data Visualization
Show steps
-
Collect a variety of data sets from different sources.
-
Create visualizations for each data set using different chart types and techniques.
-
Write descriptions and provide context for each visualization.
-
Share your portfolio with others for feedback and improvement.
Explore advanced visualization techniques
Show steps
Further understanding and skills can be gained by learning about specialized and advanced techniques
Browse courses on
3D Visualization
Show steps
-
Learn about a new advanced visualization technique
-
Find a tutorial and follow along
-
Apply the technique to a dataset
Create a data visualization dashboard
Show steps
Creating a dashboard will challenge you to apply your data visualization skills
Browse courses on
Data Visualization
Show steps
-
Design the dashboard layout
-
Gather and prepare data
-
Implement visualizations and interactivity
Participate in a data visualization competition
Show steps
Challenge yourself and showcase your skills by participating in a data visualization competition that requires you to create impactful and effective visualizations.
Browse courses on
Data Visualization
Show steps
-
Identify and register for data visualization competitions that align with your interests.
-
Gather and analyze a data set provided by the competition organizers.
-
Design and create data visualizations that effectively communicate insights and tell a compelling story.
-
Submit your visualizations and supporting documentation to the competition.
Contribute to an open-source data visualization library
Show steps
Enhance your understanding of data visualization techniques and contribute to the community by making contributions to an open-source data visualization library, such as Matplotlib or Seaborn.
Browse courses on
Data Visualization
Show steps
-
Choose an open-source data visualization library that aligns with your interests.
-
Review the library's documentation and contribute code improvements or bug fixes.
-
Suggest new features or enhancements to the library and contribute code to implement them.
Contribute to open-source data visualization projects
Show steps
Contributing to open-source projects will expose you to real-world data visualization challenges
Browse courses on
Open Source
Show steps
-
Find open-source data visualization projects
-
Identify areas where you can contribute
-
Submit pull requests with your contributions
Study graphing techniques
Show steps
Revisiting and practicing this skill before class can help those who may be unfamiliar or in need of a refresher
Browse courses on
Graphing
Show steps
Show steps
Show steps
- Review scatter and bar graphs
- Explore different graph types and use cases
- Visualize sample datasets using graphs
- Practice creating graphs using Python libraries
Review basic Python programming concepts
Show steps
Ensure a solid foundation in Python programming by reviewing basic concepts and syntax.
Browse courses on
Python Programming
Show steps
Show steps
Show steps
- Review online tutorials or documentation on Python basics.
- Practice writing simple Python programs.
- Test your understanding by solving coding exercises.
- Seek help from online forums or mentors if needed.
Review Python fundamentals
Show steps
Prepare for success in this course by reviewing the fundamentals of Python, including data types, variables, and control flow.
Browse courses on
Python
Show steps
Show steps
Show steps
- Review online tutorials or documentation on Python basics.
- Complete practice exercises or coding challenges to test your understanding.
25 other activities
Expand to see all activities and additional details
Show all 28 activities
Refresh Python programming skills
Show steps
Start the course with a strong foundation in Python programming to increase comprehension and problem-solving skills.
Browse courses on
Python
Show steps
Show steps
Show steps
- Review Python syntax and data structures
- Practice solving Python coding challenges
Review basic Python syntax and structures
Show steps
Brushing up on basic syntax will make learning more advanced topics easier and quicker
Browse courses on
Python Syntax
Show steps
Show steps
Show steps
- Go over Python tutorials for beginners
- Complete practice problems and exercises
Organize your course material
Show steps
Gather, review, and organize your notes, assignments, quizzes, and exams.
Show steps
Show steps
Show steps
- Gather all of your course materials.
- Review all of your materials to get an understanding of all of the topics.
- Organize your materials in a way makes sense to you.
Participate in online discussion forums
Show steps
Engage with peers and experts in the field by participating in online discussion forums related to data visualization.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Join online discussion forums or groups.
- Ask questions, share insights, and engage in discussions.
- Learn from the experiences and perspectives of others.
Practice data visualization with Matplotlib
Show steps
Deepen your understanding of Matplotlib by completing guided tutorials and exercises that cover creating various types of data visualizations.
Browse courses on
Matplotlib
Show steps
Show steps
Show steps
- Follow tutorials on creating basic plots, such as line charts and bar charts.
- Experiment with different Matplotlib functions to customize the appearance and functionality of your visualizations.
- Solve coding challenges that require you to create data visualizations from scratch.
Explore Matplotlib tutorials
Show steps
Matplotlib is an essential library for data visualization in Python
Browse courses on
Matplotlib
Show steps
Show steps
Show steps
- Follow along with Matplotlib tutorials
- Experiment with Matplotlib functions
Follow the Matplotlib documentation
Show steps
Find tutorials and other helpful documentation to guide you through using the Matplotlib library.
Browse courses on
Matplotlib
Show steps
Show steps
Show steps
- Go to the Matplotlib documentation website.
- Find the tutorial section.
- Start following the tutorials that are most relevant to the topics you are studying in the course.
Create visualizations from sample data
Show steps
Familiarize yourself with the basics of data visualization by creating visualizations from sample datasets.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Download sample data from the course website.
- Import the data into a Python notebook.
- Use Matplotlib or Seaborn to create visualizations of the data.
- Interpret the visualizations and identify patterns and trends in the data.
Attend a data visualization workshop
Show steps
Gain practical experience and insights from experts by attending a data visualization workshop that covers advanced techniques and best practices.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Research and identify relevant data visualization workshops in your area or online.
- Register for a workshop that aligns with your learning goals and interests.
- Actively participate in the workshop, taking notes and asking questions.
Code and analyze data visualizations
Show steps
Coding exercises will increase familiarity with key concepts and reinforce understanding
Show steps
Show steps
Show steps
- Create visualizations using Matplotlib and Seaborn
- Analyze and interpret data from visualizations
- Build interactive data visualizations
- Practice using libraries to customize and format visualizations
Organize and expand course materials
Show steps
Deepen your understanding of course materials by organizing, expanding, and reviewing notes, assignments, quizzes, and exams.
Show steps
Show steps
Show steps
- Gather and organize all course materials.
- Expand on notes by adding additional explanations and examples.
- Create summaries of key concepts and formulas.
- Review materials regularly to reinforce learning.
Collaborate on a data visualization project
Show steps
Working with a peer can result in a deeper, collaborative understanding of concepts
Show steps
Show steps
Show steps
- Find a partner with complementary skills
- Choose a dataset and define project goals
- Divide tasks and work on the visualizations
- Consolidate and present your findings
Practice creating visualizations with Matplotlib
Show steps
Practice is key to mastering data visualization techniques
Browse courses on
Matplotlib
Show steps
Show steps
Show steps
- Recreate visualizations from examples
- Create visualizations from scratch
Visualize data using different chart types
Show steps
Expand your data visualization skills by creating different types of charts, such as bar charts, line charts, scatterplots, and histograms.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Learn about different chart types and their uses.
- Choose appropriate chart types for different types of data.
- Create visualizations using various chart types in Python.
- Evaluate the effectiveness of different chart types in communicating data.
Develop a data visualization dashboard
Show steps
Apply your visualization skills to create a real-world data visualization dashboard that provides insights and value to an audience.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Identify a business problem or opportunity that can be addressed through data visualization.
- Gather and clean the necessary data.
- Design and build a dashboard using appropriate visualization techniques and tools.
- Deploy and share the dashboard with stakeholders.
Build a data visualization portfolio
Show steps
A collection of visualizations will showcase your skills and solidify your learning
Show steps
Show steps
Show steps
- Create a repository to store your visualizations
- Visualize data from different sources
- Write a brief description for each visualization
- Get feedback from peers or mentors
Explore online tutorials on advanced data visualization techniques
Show steps
Enhance your data visualization skills by exploring online tutorials on advanced techniques, such as interactive visualizations and data storytelling.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Search for online tutorials on advanced data visualization techniques.
- Follow the tutorials and implement the techniques in your own projects.
- Experiment with different techniques and explore their capabilities.
- Share your findings and insights with others.
create data visualizations using the Matplotlib library
Show steps
Reinforce your understanding of data visualization techniques by creating visualizations using the Matplotlib library.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Choose a dataset to visualize.
- Import the Matplotlib library.
- Use the Matplotlib library to create a visualization of the dataset.
- Save your visualization as an image file.
Create a data visualization portfolio
Show steps
Showcase your data visualization skills by creating a portfolio that includes a variety of visualizations you've created using Matplotlib.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Gather a collection of different data sets that represent various types of data.
- Create visualizations for each data set, using appropriate chart types and techniques.
- Write brief descriptions for each visualization, explaining the insights it provides.
- Host your portfolio online or share it with others for feedback.
Build a data visualization portfolio
Show steps
Showcase your data visualization skills by creating a portfolio of visualizations that demonstrate your abilities and understanding of data presentation.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Collect a variety of data sets from different sources.
- Create visualizations for each data set using different chart types and techniques.
- Write descriptions and provide context for each visualization.
- Share your portfolio with others for feedback and improvement.
Explore advanced visualization techniques
Show steps
Further understanding and skills can be gained by learning about specialized and advanced techniques
Browse courses on
3D Visualization
Show steps
Show steps
Show steps
- Learn about a new advanced visualization technique
- Find a tutorial and follow along
- Apply the technique to a dataset
Create a data visualization dashboard
Show steps
Creating a dashboard will challenge you to apply your data visualization skills
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Design the dashboard layout
- Gather and prepare data
- Implement visualizations and interactivity
Participate in a data visualization competition
Show steps
Challenge yourself and showcase your skills by participating in a data visualization competition that requires you to create impactful and effective visualizations.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Identify and register for data visualization competitions that align with your interests.
- Gather and analyze a data set provided by the competition organizers.
- Design and create data visualizations that effectively communicate insights and tell a compelling story.
- Submit your visualizations and supporting documentation to the competition.
Contribute to an open-source data visualization library
Show steps
Enhance your understanding of data visualization techniques and contribute to the community by making contributions to an open-source data visualization library, such as Matplotlib or Seaborn.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Choose an open-source data visualization library that aligns with your interests.
- Review the library's documentation and contribute code improvements or bug fixes.
- Suggest new features or enhancements to the library and contribute code to implement them.
Contribute to open-source data visualization projects
Show steps
Contributing to open-source projects will expose you to real-world data visualization challenges
Browse courses on
Open Source
Show steps
Show steps
Show steps
- Find open-source data visualization projects
- Identify areas where you can contribute
- Submit pull requests with your contributions
Career center
Learners who complete Visualización de Datos con Python will develop knowledge and skills
that may be useful to these careers:
Data Visualization Engineer
Data Visualization Engineer
Data Visualization Engineers specialize in designing and developing data visualization solutions for various applications. They use their expertise in data visualization to create interactive and engaging visualizations that communicate data insights effectively. The Visualización de Datos con Python course can help Data Visualization Engineers enhance their skills in data visualization, enabling them to create more sophisticated and impactful visualizations.
Data Analyst
Data Analyst
Data Analysts use their expertise in data visualization to help organizations make sense of large and complex datasets. They use statistical techniques and programming languages to analyze data and create visual representations that communicate key insights and trends. The Visualización de Datos con Python course can help Data Analysts enhance their skills in data visualization, enabling them to create more effective and engaging data visualizations that support informed decision-making.
Data Scientist
Data Scientist
Data Scientists use their knowledge of data visualization to communicate complex insights and findings to stakeholders across the organization. They use visual representations to present data in a clear and concise manner, making it easier for decision-makers to understand the implications of data-driven insights. The Visualización de Datos con Python course can help Data Scientists develop their data visualization skills, enabling them to create compelling visualizations that effectively convey data-driven insights.
Business Analyst
Business Analyst
Business Analysts use data visualization to communicate complex business concepts and insights to stakeholders. They use visual representations to present data in a clear and concise manner, making it easier for decision-makers to understand the implications of data-driven insights. The Visualización de Datos con Python course can help Business Analysts develop their data visualization skills, enabling them to create compelling visualizations that effectively convey data-driven insights.
Product Manager
Product Manager
Product Managers use data visualization to communicate product insights and user feedback to stakeholders. They use visual representations to present data in a clear and concise manner, making it easier for decision-makers to understand the implications of data-driven insights. The Visualización de Datos con Python course can help Product Managers develop their data visualization skills, enabling them to create compelling visualizations that effectively convey product-related insights.
Market Researcher
Market Researcher
Market Researchers use data visualization to communicate research insights and trends to stakeholders. They use visual representations to present data in a clear and concise manner, making it easier for decision-makers to understand the implications of data-driven insights. The Visualización de Datos con Python course can help Market Researchers develop their data visualization skills, enabling them to create compelling visualizations that effectively convey market research insights.
Financial Analyst
Financial Analyst
Financial Analysts use data visualization to communicate financial insights and trends to stakeholders. They use visual representations to present data in a clear and concise manner, making it easier for decision-makers to understand the implications of data-driven insights. The Visualización de Datos con Python course can help Financial Analysts develop their data visualization skills, enabling them to create compelling visualizations that effectively convey financial insights.
Consultant
Consultant
Consultants use data visualization to communicate insights and recommendations to clients. They use visual representations to present data in a clear and concise manner, making it easier for clients to understand the implications of data-driven insights. The Visualización de Datos con Python course can help Consultants develop their data visualization skills, enabling them to create compelling visualizations that effectively convey consulting insights.
UX Designer
UX Designer
UX Designers use data visualization to communicate user research insights and design recommendations to stakeholders. They use visual representations to present data in a clear and concise manner, making it easier for decision-makers to understand the implications of data-driven insights. The Visualización de Datos con Python course can help UX Designers develop their data visualization skills, enabling them to create compelling visualizations that effectively convey user research insights.
Journalist
Journalist
Journalists use data visualization to communicate complex stories and insights to readers. They use visual representations to present data in a clear and concise manner, making it easier for readers to understand complex issues. The Visualización de Datos con Python course can help Journalists develop their data visualization skills, enabling them to create compelling visualizations that effectively convey news stories and insights.
Teacher
Teacher
Teachers use data visualization to communicate complex concepts and ideas to students. They use visual representations to present data in a clear and concise manner, making it easier for students to understand complex subjects. The Visualización de Datos con Python course can help Teachers develop their data visualization skills, enabling them to create compelling visualizations that effectively convey educational content.
Researcher
Researcher
Researchers use data visualization to communicate research findings and insights to stakeholders. They use visual representations to present data in a clear and concise manner, making it easier for decision-makers to understand the implications of data-driven insights. The Visualización de Datos con Python course can help Researchers develop their data visualization skills, enabling them to create compelling visualizations that effectively convey research insights.
Software Engineer
Software Engineer
Software Engineers use data visualization to communicate complex technical concepts and design decisions to stakeholders. They use visual representations to present data in a clear and concise manner, making it easier for decision-makers to understand the implications of data-driven insights. The Visualización de Datos con Python course may help Software Engineers develop their data visualization skills, enabling them to create compelling visualizations that effectively convey technical insights.
Data Engineer
Data Engineer
Data Engineers use data visualization to communicate data pipeline design and implementation to stakeholders. They use visual representations to present data in a clear and concise manner, making it easier for decision-makers to understand the implications of data-driven insights. The Visualización de Datos con Python course may help Data Engineers develop their data visualization skills, enabling them to create compelling visualizations that effectively convey data engineering insights.
Database Administrator
Database Administrator
Database Administrators use data visualization to communicate database design and performance to stakeholders. They use visual representations to present data in a clear and concise manner, making it easier for decision-makers to understand the implications of data-driven insights. The Visualización de Datos con Python course may help Database Administrators develop their data visualization skills, enabling them to create compelling visualizations that effectively convey database insights.
For more career information including salaries, visit:
OpenCourser.com/course/zytb6q/visualizacion
Reading list
We've selected 11 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Visualización de Datos con Python .
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This textbook by Nathan Yau provides comprehensive coverage of data visualization techniques and principles, with a focus on modern tools and practices. It offers a solid foundation for understanding and creating effective data visualizations.
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Edward R. Tufte's classic work on data visualization emphasizes the principles of design and clarity in presenting statistical information. It offers valuable insights into the effective communication of data through visual means.
Provides a comprehensive introduction to ggplot2, a powerful data visualization library in R. It covers the basics of creating and customizing various types of plots, including ggplot2's grammar of graphics approach.
Provides a comprehensive introduction to Python for data analysis, including data manipulation, visualization, and statistical modeling. It offers a solid foundation for using Python in data-related tasks.
Covers data visualization using Python and JavaScript, providing a comprehensive overview of techniques for creating interactive and dynamic visualizations. It includes topics such as D3.js, Bokeh, and Plotly.
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Provides a collection of recipes for creating various types of visualizations in R. It offers practical solutions to common data visualization challenges and demonstrates best practices for effective visual communication.
Provides a solid foundation for understanding the principles and techniques of data visualization. It covers topics such as visual perception, color theory, and typography, offering a comprehensive guide to creating clear and meaningful visualizations.
Covers interactive data visualization for the web using JavaScript and D3.js. It provides a comprehensive guide to creating interactive and engaging visualizations that can be deployed on the web.
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Explores the field of visual complexity, focusing on the visualization of large-scale data sets and the patterns and relationships that emerge from them. It offers a unique perspective on data visualization and its role in understanding complex systems.
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Provides guidance on designing effective information dashboards that clearly communicate data and insights. It covers topics such as dashboard design principles, visual perception, and data storytelling, offering valuable insights for creating impactful dashboards.
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Offers a collection of articles and essays on data visualization, design, and statistics from Nathan Yau's popular FlowingData blog. It provides practical tips and insights for creating effective and engaging visualizations.
For more information about how these books relate to this course, visit:
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Via
Coursera
Institutions
IBM
IBM Skills Network
Instructor
Alex Aklson
This course belongs to a
collection
called
Ciencia de Datos de IBM. It's comprised of nine courses:
- Análisis de datos con Python
- Aprendizaje Automático con Python
- Python para Data Science y AI
- Bases de datos y SQL para ciencia de datos
- Visualización de Datos con Python (viewing)
- Herramientas para la ciencia de datos
- Metodología de la ciencia de datos
- Ciencia de Datos Aplicada - Curso Capstone
- ¿Qué es la ciencia de datos?
Good to know
Reinforces existing skills and knowledge in data visualization with Python libraries, which are industry standards
Suitable for learners with a background in data analysis and an interest in improving their data visualization skills
Taught by Alex Akslon, who has extensive experience in data visualization
Course content focuses on practical applications, ensuring that learners can immediately apply their knowledge
Utilizes a project-based approach, providing learners with hands-on experience in visualizing data
Optionally, learners can subscribe for $39 per month to access exclusive materials and a certificate
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