Python Data Visualization & Interactive Dashboards Online (Self-Paced)
IDUZY

Self-paced online training with expert support

Gain hands-on experience creating data visualizations using Python libraries like Matplotlib, Seaborn, and Plotly. You'll build interactive dashboards with Dash and work on real-world datasets to analyze and present data effectively. This self-paced course is ideal for those with basic Python knowledge looking to enhance their data analysis skills.

$1,695 24 clock hours Live Support Start anytime

This course includes

  • 24 hours of project-based training from experts
  • Answers from real instructors
  • Access to class recordings (30 days)
  • Verified digital certificate of completion
  • Learn at an accredited institution

This course is self-paced. For live online or in-person instruction, take Python Data Visualization & Interactive Dashboards.

In this course, you’ll learn to gather, manipulate, and analyze real-world data through hands-on projects. The class begins with the Python libraries NumPy and Pandas, then moves on to plotting solutions with a focus on data visualization. Alongside traditional plotting tools like Matplotlib and Seaborn, you’ll explore Plotly and Dash Enterprise, a powerful platform for creating dynamic dashboards.

Throughout the course, you’ll gain experience by working on real-world projects that you can deploy online using the Heroku server and GitHub. Hosting an analytical project on GitHub showcases your data science skills and can help meet requirements for future employment. Potential employers will be interested in seeing your coding methods and data analysis approaches.

Each day of the course is split into two parts. In the first half, you’ll learn new concepts. In the second, you’ll apply them to a project on a topic of your choice—such as your professional field or another area of interest. The instructor will guide you in finding a suitable dataset, share best practices, and assist with coding.

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This course has a prerequisite

Participants should attend the Python for Data Science Course Online (Self-Paced) prior to attending this course.

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