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Reshma Mehta
I started to use Observable and create a notebook there. I'd like to present the notebook and my learnings using vega lite for data visualization and some of the awesome features that Observable has.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Introduces advanced topics relevant to those interested in visualization, such as Vega-Lite
Suitable for those looking to enhance their data visualization skills and create interactive notebooks using Observable
Taught by Reshma Mehta, an experienced instructor in data visualization and coding
May require some prior knowledge of data visualization concepts and tools
Focuses on the use of Vega-Lite, which may not be widely used in all industries

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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 Experimenting with Observable with these activities:
Effective Data Visualization
This book provides a comprehensive overview of the principles and best practices of data visualization. It will help you to create visualizations that are clear, concise, and effective.
Show steps
  • Read the book.
  • Summarize the key concepts of the book.
  • Apply the concepts to your own data visualization projects.
Vega Lite Bootcamp
Vega-Lite will be an important tool for visualizing data in this course. This Bootcamp will help you to strengthen your foundation and ensure a successful learning experience.
Show steps
  • Complete the online Vega-Lite tutorial.
  • Build a Vega-Lite visualization using a provided dataset.
  • Share your visualization with a classmate for feedback.
Vega-Lite Coding Challenges
These coding challenges will help you to practice your Vega-Lite skills and improve your understanding of the language.
Show steps
  • Solve the coding challenges.
  • Review your solutions with a classmate.
  • Apply the concepts to your own data visualization projects.
Five other activities
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Create an Interactive Dashboard with Observable
Observable is a powerful tool for creating interactive data visualizations. This tutorial will guide you through the process of building a dashboard that can help you explore and understand your data.
Show steps
  • Follow the Observable tutorial on creating a dashboard.
  • Experiment with different data sources and visualizations.
  • Share your dashboard with a classmate for feedback.
Data Visualization Study Group
Meeting with peers to discuss data visualization concepts will help you to deepen your understanding of the material and to learn from others.
Browse courses on Data Visualization
Show steps
  • Form a study group with other students in the course.
  • Meet regularly to discuss the course material.
  • Work together on data visualization projects.
Data Visualization Project
This project will allow you to apply the skills you have learned in this course to a real-world dataset. You will create an interactive visualization that can help you explore and understand the data.
Browse courses on Data Visualization
Show steps
  • Choose a dataset that you are interested in.
  • Clean and prepare the data for visualization.
  • Create a Vega-Lite visualization using Observable.
  • Write a report that describes your visualization and the insights that you gained from it.
Vega-Lite Workshop
Attending a Vega-Lite workshop is a great way to learn from experts and to get hands-on experience with the library.
Show steps
  • Find a Vega-Lite workshop in your area.
  • Register for the workshop.
  • Attend the workshop and participate in the activities.
Contribute to the Vega-Lite Project
Contributing to the Vega-Lite project is a great way to learn about the inner workings of the library and to make a valuable contribution to the community.
Show steps
  • Find an issue on the Vega-Lite GitHub repository.
  • Fix the issue and submit a pull request.
  • Review the feedback on your pull request and make any necessary changes.
  • Get your pull request merged into the Vega-Lite project.

Career center

Learners who complete Experimenting with Observable will develop knowledge and skills that may be useful to these careers:
Data Analyst
A Data Analyst is responsible for collecting, cleaning, and analyzing data to identify trends and patterns. This course can help build a foundation in data visualization, an important skill for Data Analysts who need to communicate their findings effectively. Familiarity with Observable and Vega Lite will be a bonus for any Data Analyst.
Data Scientist
Data Scientists use scientific methods to extract knowledge and insights from data. This course can help build a foundation in data visualization, an important skill for Data Scientists who need to communicate their findings effectively. Familiarity with Observable and Vega Lite will be a bonus for any Data Scientist.
Statistician
Statisticians collect, analyze, interpret, and present data. This course may be useful for Statisticians who are interested in learning more about data visualization and how to use it to communicate their findings more effectively.
Data Architect
Data Architects design and manage data systems. This course may be useful for Data Architects who are interested in learning more about data visualization and how to use it to communicate their designs more effectively.
Software Engineer
Software Engineers design, develop, and maintain software systems. This course may be useful for Software Engineers who are interested in learning more about data visualization and how to use it to improve their applications.
Product Manager
Product Managers oversee the development and launch of products. This course may be useful for Product Managers who are interested in learning more about data visualization and how to use it to communicate their product vision and roadmap more effectively.
Data Engineer
Data Engineers design, build, and maintain data pipelines and databases. This course may be useful for Data Engineers who are interested in learning more about data visualization and how to use it to monitor their pipelines and databases.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. This course may be useful for Quantitative Analysts who are interested in learning more about data visualization and how to use it to communicate their findings more effectively.
Market Researcher
Market Researchers gather and analyze data about consumers and markets. This course may be useful for Market Researchers who are interested in learning more about data visualization and how to use it to communicate their findings more effectively.
User Experience Designer
User Experience Designers design and evaluate user interfaces. This course may be useful for User Experience Designers who are interested in learning more about data visualization and how to use it to improve the user experience of their products.
Information Architect
Information Architects design and manage information systems. This course may be useful for Information Architects who are interested in learning more about data visualization and how to use it to communicate their designs more effectively.
Visual Designer
Visual Designers create visual representations of data. This course may be useful for Visual Designers who are interested in learning more about data visualization and how to use it to create more effective and visually appealing designs.
Interactive Designer
Interactive Designers design and develop interactive experiences. This course may be useful for Interactive Designers who are interested in learning more about data visualization and how to use it to create more engaging and informative experiences.
Data Journalist
Data Journalists use data to tell stories and communicate information. This course may be useful for Data Journalists who are interested in learning more about data visualization and how to use it to create more engaging and informative stories.
Business Analyst
Business Analysts analyze business processes and data to identify areas for improvement. This course may be useful for Business Analysts who are interested in learning more about data visualization and how to use it to communicate their findings more effectively.

Reading list

We've selected nine 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 Experimenting with Observable.
Is the definitive guide to D3.js, a powerful JavaScript library for data visualization. It covers all aspects of D3, from the basics of creating charts to advanced techniques for creating complex visualizations.
Provides a comprehensive introduction to Python for data analysis. It covers all aspects of data analysis, from data cleaning and wrangling to data visualization and modeling.
Provides a comprehensive introduction to R for data science. It covers all aspects of data analysis, from data cleaning and wrangling to data visualization and modeling.
Provides a comprehensive introduction to Bayesian statistics using R and Stan. It covers all aspects of Bayesian statistics, from the basics of probability and inference to advanced topics such as hierarchical modeling and Markov chain Monte Carlo.
Provides a comprehensive introduction to deep learning using Python. It covers all aspects of deep learning, from the basics of neural networks to advanced topics such as convolutional neural networks and recurrent neural networks.
Provides a comprehensive introduction to TensorFlow, a popular open-source machine learning library. It covers all aspects of TensorFlow, from the basics of neural networks to advanced topics such as convolutional neural networks and recurrent neural networks.
Provides a comprehensive introduction to deep learning using R. It covers all aspects of deep learning, from the basics of neural networks to advanced topics such as convolutional neural networks and recurrent neural networks.
Provides a comprehensive introduction to deep learning using Fastai and PyTorch. It covers all aspects of deep learning, from the basics of neural networks to advanced topics such as convolutional neural networks and recurrent neural networks.

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