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Mo Rebaie
In this two-hour long project-based course, you will learn Data Visualization techniques in Data Science. By the end of this project, you will have created and visualized scatter plots, line plots, bar charts, subplots, box plots, histograms, heat maps, and...
Read more
In this two-hour long project-based course, you will learn Data Visualization techniques in Data Science. By the end of this project, you will have created and visualized scatter plots, line plots, bar charts, subplots, box plots, histograms, heat maps, and...
Read more
In this two-hour long project-based course, you will learn Data Visualization techniques in Data Science. By the end of this project, you will have created and visualized scatter plots, line plots, bar charts, subplots, box plots, histograms, heat maps, and animations.
This class is for learners who want to use Python for Data Visualization and Plots, and for learners who are currently taking a basic machine learning course or have already finished a machine learning course and are searching for a practical data visualization project course. Also, this project provides learners with basic knowledge about data visualization techniques and improves their skills in creating various types of charts and plots which helps them in fulfilling their career goals by adding this project to their portfolios.
Register for this course and see more details by visiting:
OpenCourser.com/course/l8osve/plots
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possible dealbreakers
Develops professional skills in data visualization and improves skills in creating charts and plots
Provides learners with basic knowledge about data visualization techniques
Targeted at learners with basic machine learning knowledge who seek hands-on data visualization projects
Emphasizes Python for data visualization and plots
Utilizes a project-based approach, focusing on practical application
Teaches various data visualization techniques, including scatter plots, line plots, and heat maps
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Reviews summary
Data visualization with python
Learners agreed that this project-based course is a good introduction to using Python for data visualization. It provides learners with the experience to create a variety of charts and add them to their portfolios to improve their career prospects. It's important to note that while the videos don't provide much explanation, you can learn how to create various charts by executing the cells in the notebook.
Project-based learning
Helps build portfolio
Great for beginners
"This is an awesome course for Data Visualization and in a short time anybody can learn data visualization."
Potential technical issues with screen size and audio quality
"Rhyme is terrible for a 12.5" laptop screen. I cannnot read the text properly."
"Everytime I type something into the virtual desktop, my screen gets blurry for a split-second."
"the audio quality is very bad."
Videos could use more explanation
"The videos also don't explain much of each chart type."
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 Plots (Graphics) for Data Science with these
activities:
Read Data Science from Scratch
Show steps
Get familiar with the concepts of data science, which will help you understand the bigger picture and make sense of the tools you will use in this course.
View
Data Science from Scratch: First Principles...
on Amazon
Show steps
-
Read the first three chapters.
-
Complete the exercises provided in the book.
Follow the Data Visualization with Matplotlib tutorial
Show steps
Following a tutorial will provide you with a structured approach to learn Matplotlib, which is a valuable tool for data visualization in Python.
Browse courses on
Data Visualization
Show steps
-
Go to the official Matplotlib website.
-
Find the Data Visualization with Matplotlib tutorial.
-
Follow the tutorial step-by-step.
-
Complete the exercises provided in the tutorial.
Create a scatter plot of your favorite dataset
Show steps
Creating a scatter plot will help you understand the relationship between two variables, improving your understanding of data visualization.
Browse courses on
Data Visualization
Show steps
-
Import the necessary libraries.
-
Load the dataset.
-
Create the scatter plot using Matplotlib or Seaborn.
-
Label the axes and add a title.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Solve Python coding challenges on LeetCode
Show steps
Solving coding challenges will sharpen your Python skills and improve your problem-solving abilities, which are essential for data science.
Browse courses on
Python
Show steps
-
Create an account on LeetCode.
-
Choose a topic.
-
Solve the easy problems first.
-
Check the discussion section for hints.
Attend a data visualization workshop
Show steps
Attending a workshop will provide you with hands-on experience and the opportunity to learn from experts in the field, enhancing your understanding of data visualization techniques.
Browse courses on
Data Visualization
Show steps
-
Find a relevant workshop.
-
Register for the workshop.
-
Attend the workshop.
-
Participate in discussions and ask questions.
Create an interactive dashboard using Tableau
Show steps
Creating an interactive dashboard will allow you to visualize data in a meaningful way, helping you consolidate your learning and showcase your skills.
Browse courses on
Data Visualization
Show steps
-
Gather the necessary data.
-
Connect to the data source.
-
Create the dashboard using Tableau.
-
Add visualizations and filters.
-
Publish the dashboard.
Create a collection of data visualization resources
Show steps
Creating a compilation of resources will provide you with a valuable collection of materials for future reference and continued learning in data visualization.
Browse courses on
Data Visualization
Show steps
-
Gather resources from different sources.
-
Organize the resources into categories.
-
Create a document or spreadsheet to store the resources.
-
Share the compilation with others.
Read Data Science from Scratch
Show steps
Get familiar with the concepts of data science, which will help you understand the bigger picture and make sense of the tools you will use in this course.
View
Data Science from Scratch: First Principles...
on Amazon
Show steps
Show steps
Show steps
- Read the first three chapters.
- Complete the exercises provided in the book.
Follow the Data Visualization with Matplotlib tutorial
Show steps
Following a tutorial will provide you with a structured approach to learn Matplotlib, which is a valuable tool for data visualization in Python.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Go to the official Matplotlib website.
- Find the Data Visualization with Matplotlib tutorial.
- Follow the tutorial step-by-step.
- Complete the exercises provided in the tutorial.
Create a scatter plot of your favorite dataset
Show steps
Creating a scatter plot will help you understand the relationship between two variables, improving your understanding of data visualization.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Import the necessary libraries.
- Load the dataset.
- Create the scatter plot using Matplotlib or Seaborn.
- Label the axes and add a title.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Solve Python coding challenges on LeetCode
Show steps
Solving coding challenges will sharpen your Python skills and improve your problem-solving abilities, which are essential for data science.
Browse courses on
Python
Show steps
Show steps
Show steps
- Create an account on LeetCode.
- Choose a topic.
- Solve the easy problems first.
- Check the discussion section for hints.
Attend a data visualization workshop
Show steps
Attending a workshop will provide you with hands-on experience and the opportunity to learn from experts in the field, enhancing your understanding of data visualization techniques.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Find a relevant workshop.
- Register for the workshop.
- Attend the workshop.
- Participate in discussions and ask questions.
Create an interactive dashboard using Tableau
Show steps
Creating an interactive dashboard will allow you to visualize data in a meaningful way, helping you consolidate your learning and showcase your skills.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Gather the necessary data.
- Connect to the data source.
- Create the dashboard using Tableau.
- Add visualizations and filters.
- Publish the dashboard.
Create a collection of data visualization resources
Show steps
Creating a compilation of resources will provide you with a valuable collection of materials for future reference and continued learning in data visualization.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Gather resources from different sources.
- Organize the resources into categories.
- Create a document or spreadsheet to store the resources.
- Share the compilation with others.
Career center
Learners who complete Plots (Graphics) for Data Science will develop knowledge and skills
that may be useful to these careers:
Data Visualization Engineer
Data Visualization Engineer
A Data Visualization Engineer is responsible for designing and developing data visualizations that communicate insights and trends from complex data. This course provides a solid foundation in data visualization techniques, including scatter plots, line plots, bar charts, subplots, box plots, histograms, heat maps, and animations. These skills are essential for Data Visualization Engineers to effectively communicate data-driven insights to stakeholders.
Data Scientist
Data Scientist
Data Scientists use data to solve business problems and make informed decisions. This course provides Data Scientists with the skills to visualize and analyze data, which is essential for identifying trends, patterns, and insights from complex data. The course covers a variety of visualization techniques, including scatter plots, line plots, bar charts, subplots, box plots, histograms, heat maps, and animations.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns. This course provides Data Analysts with the skills to visualize and analyze data, which is essential for communicating insights to stakeholders. The course covers a variety of visualization techniques, including scatter plots, line plots, bar charts, subplots, box plots, histograms, heat maps, and animations.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts use data to help businesses make better decisions. This course provides Business Intelligence Analysts with the skills to visualize and analyze data, which is essential for identifying trends, patterns, and insights from complex data. The course covers a variety of visualization techniques, including scatter plots, line plots, bar charts, subplots, box plots, histograms, heat maps, and animations.
Statistician
Statistician
Statisticians collect, analyze, and interpret data to provide insights into a variety of topics. This course provides Statisticians with the skills to visualize and analyze data, which is essential for communicating insights to stakeholders. The course covers a variety of visualization techniques, including scatter plots, line plots, bar charts, subplots, box plots, histograms, heat maps, and animations.
Financial Analyst
Financial Analyst
Financial Analysts use data to make investment decisions. This course provides Financial Analysts with the skills to visualize and analyze data, which is essential for identifying trends, patterns, and insights from complex financial data. The course covers a variety of visualization techniques, including scatter plots, line plots, bar charts, subplots, box plots, histograms, heat maps, and animations.
Market Researcher
Market Researcher
Market Researchers collect and analyze data to understand consumer behavior. This course provides Market Researchers with the skills to visualize and analyze data, which is essential for identifying trends, patterns, and insights from complex data. The course covers a variety of visualization techniques, including scatter plots, line plots, bar charts, subplots, box plots, histograms, heat maps, and animations.
User Experience Researcher
User Experience Researcher
User Experience Researchers collect and analyze data to understand user behavior and improve the user experience of products and services. This course provides User Experience Researchers with the skills to visualize and analyze data, which is essential for identifying trends, patterns, and insights from complex data. The course covers a variety of visualization techniques, including scatter plots, line plots, bar charts, subplots, box plots, histograms, heat maps, and animations.
Product Manager
Product Manager
Product Managers are responsible for the development and management of products. This course provides Product Managers with the skills to visualize and analyze data, which is essential for understanding user needs, identifying trends, and making informed decisions about product development. The course covers a variety of visualization techniques, including scatter plots, line plots, bar charts, subplots, box plots, histograms, heat maps, and animations.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. This course provides Software Engineers with the skills to visualize and analyze data, which is essential for understanding user needs, identifying trends, and making informed decisions about software development. The course covers a variety of visualization techniques, including scatter plots, line plots, bar charts, subplots, box plots, histograms, heat maps, and animations.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data systems. This course provides Data Engineers with the skills to visualize and analyze data, which is essential for understanding data requirements, identifying trends, and making informed decisions about data system design. The course covers a variety of visualization techniques, including scatter plots, line plots, bar charts, subplots, box plots, histograms, heat maps, and animations.
Database Administrator
Database Administrator
Database Administrators are responsible for the management and maintenance of databases. This course provides Database Administrators with the skills to visualize and analyze data, which is essential for understanding data requirements, identifying trends, and making informed decisions about database design. The course covers a variety of visualization techniques, including scatter plots, line plots, bar charts, subplots, box plots, histograms, heat maps, and animations.
Information Architect
Information Architect
Information Architects design and organize information systems. This course provides Information Architects with the skills to visualize and analyze data, which is essential for understanding user needs, identifying trends, and making informed decisions about information system design. The course covers a variety of visualization techniques, including scatter plots, line plots, bar charts, subplots, box plots, histograms, heat maps, and animations.
Technical Writer
Technical Writer
Technical Writers create documentation for software and other technical products. This course provides Technical Writers with the skills to visualize and analyze data, which is essential for understanding complex technical information and communicating it effectively to users. The course covers a variety of visualization techniques, including scatter plots, line plots, bar charts, subplots, box plots, histograms, heat maps, and animations.
Science Writer
Science Writer
Science Writers communicate complex scientific information to non-scientific audiences. This course provides Science Writers with the skills to visualize and analyze data, which is essential for understanding complex scientific data and communicating it effectively to non-scientific audiences. The course covers a variety of visualization techniques, including scatter plots, line plots, bar charts, subplots, box plots, histograms, heat maps, and animations.
For more career information including salaries, visit:
OpenCourser.com/course/l8osve/plots
Reading list
We've selected eight 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
Plots (Graphics) for Data Science.
Save
Classic work on data visualization. It covers a wide range of topics, including data exploration, chart types, and storytelling with data. This book valuable resource for learners who want to gain a deep understanding of data visualization.
Save
Provides a comprehensive introduction to data visualization techniques and best practices. It covers a wide range of topics, including data exploration, chart types, and storytelling with data. This book is an excellent resource for learners who want to gain a solid foundation in data visualization and those who are new to Python for Data Visualization and Plots
Provides a comprehensive introduction to the grammar of graphics. It covers a wide range of topics, including data exploration, chart types, and storytelling with data. This book valuable resource for learners who want to gain a deep understanding of data visualization.
Save
Provides a comprehensive introduction to data visualization techniques and best practices. It covers a wide range of topics, including data exploration, chart types, and storytelling with data. This book may be used to supplement this course or even replace it, fits perfectly with learners who are new to Python for Data Visualization and Plots.
Provides a comprehensive introduction to the ggplot2 package for data visualization in R. It covers a wide range of topics, including data exploration, chart types, and interactive visualizations. This book is an excellent resource for learners who want to learn how to use ggplot2 for data visualization.
Save
Provides a comprehensive introduction to data visualization with R. It covers a wide range of topics, including data exploration, chart types, and interactive visualizations. This book is an excellent resource for learners who want to learn how to use R for data visualization.
Provides a comprehensive introduction to interactive data visualization with JavaScript. It covers a wide range of topics, including data exploration, chart types, and interactive visualizations. This book is an excellent resource for learners who want to learn how to use JavaScript for data visualization.
Provides a comprehensive guide to creating effective dashboards. It covers a wide range of topics, including data exploration, dashboard design, and storytelling with data. This book valuable resource for learners who want to learn how to create effective dashboards.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/l8osve/plots
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Time
2 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Mo Rebaie
Good to know
Develops professional skills in data visualization and improves skills in creating charts and plots
Provides learners with basic knowledge about data visualization techniques
Targeted at learners with basic machine learning knowledge who seek hands-on data visualization projects
Emphasizes Python for data visualization and plots
Utilizes a project-based approach, focusing on practical application
Teaches various data visualization techniques, including scatter plots, line plots, and heat maps
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