Pragmatic Data Curriculm

     Essential Tools      Practical Machine Learning      Advanced Machine Learning      AI with TensorFlow      Data Visualization

Data Visualization

Data Visualization with Python is a live, 3-week, online boot camp in which you'll learn how to present data in a way that make sense to your entire organization. For three hours twice a week, you will learn how to build visualizations that help you understand and communicate the story of data. Drawing on the science of perception and memory, you’ll learn how to create interactive graphics in Python to develop and share insights from your data. This course also focuses on how visual components can showcase large capacities of data, the role of visualizations in data exploration, how to create information-rich interactive graphics and more. Ensure your non-technical colleagues understand the story by presenting it in clear and comprehensible ways that showcase the data and the effectiveness of your projects.

Download a copy of the syllabus to convince your manager the importance of this course

Business Benefits

Data Visualization with Python teaches you to use one of the most versatile tools to display and present your data in visual ways that make sense to your entire organization. Ensure your colleagues understand what your data says, what it means and how it can change the future of your company.

 Who Should Attend

Data analysts, business analysts, economists, researchers, software, data engineers or data managers who want to develop or strengthen data visualization skills

 Key Skills Covered

Python visualization tools, dealing with multiple scales, grid-based data aggregation, box and violin plots, non-obvious patterns in data, Fourier components, Bokeh, Plotly, Vega and Altair

 Prerequisites

To achieve the greatest benefit from this course, attendees must take Essential Tools and Practical Machine Learning or possess elementary programming knowledge.

Earn a coveted data science certification upon successful completion of class project
What You'll Learn

Over the course of 3 weeks, you get hands-on experience creating clear and understandable visual interpretations of your data.

The importance of
data visualization

Perception & visualization theory

  • Categories of visual cues
  • Probability & accessibility
  • Contextual perception & visual response

Layout & design

  • Design elements
  • Choosing the right axes & marks
  • Multiple scales

Utilizing Python visualization tools

Exploratory visualization

  • Python visualization tools
  • Non-obvious patterns in data
  • Interactivity in Jupyter notebooks

Visualizing large datasets

  • Dimensionality reduction
  • Out-of-core visualization
  • Grid-based data aggregation

Additional tools for explanatory visualizations.

Exploratory visualization

  • Interactivity for the web
  • Bokeh & Plotly
  • Altair & Vega: grammar of graphics in JSON

Deploying a data visualization application

  • Dashboarding & BI reporting
  • Bokeh server
  • Plotly dash

Netflix pragmatic live

How does someone become a modern-day data scientist for one of the biggest digital companies in the world?

Check out this podcast featuring Becky Tucker, Ph.D., senior data scientist at Netflix. See how she got her start and wound up at the world’s largest streaming service. Listen now

Read more about what other students have done with their data science education on our sister company site:

Learn more about our entire data science curriculum