Duke University

Data Visualization with Python

This course is part of Applied Python Data Engineering Specialization

Taught in English

Matt Harrison
Noah Gift
Kennedy Behrman

Instructors: Matt Harrison

2,123 already enrolled

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Course

Gain insight into a topic and learn the fundamentals

Intermediate level

Recommended experience

9 hours (approximately)
Flexible schedule
Learn at your own pace

What you'll learn

  • Apply Python, spreadsheets, and BI tooling proficiently to create visually compelling and interactive data visualizations.

  • Formulate and communicate data-driven insights and narratives through impactful visualizations and data storytelling.

  • Assess and select the most suitable visualization tools and techniques to address organizational data needs and objectives.

Details to know

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Assessments

4 quizzes

Course

Gain insight into a topic and learn the fundamentals

Intermediate level

Recommended experience

9 hours (approximately)
Flexible schedule
Learn at your own pace

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Build your subject-matter expertise

This course is part of the Applied Python Data Engineering Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
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There are 4 modules in this course

In this module, we will introduce you to the fundamentals of data visualization and provide step-by-step guidance on how to get started with creating basic plots in Excel and Google Sheets. Whether you are new to data visualization or looking to enhance your skills, this week will lay the groundwork for effective visual storytelling using these widely accessible tools.

What's included

13 videos7 readings1 quiz2 discussion prompts

In this module, you will embark on an exciting journey of learning as you explore data visualization using Pandas, Seaborn and Matplotlib. You will use Pandas and Seaborn to construct histograms, which will allow you to gain insights into the distribution of your numerical data. You will also delve into scatterplots, enabling you to visualize the relationships between different variables in your datasets and identify patterns and correlations. Lastly, you will learn how to utilize line plots to capture temporal trends and changes over time, enhancing your ability to communicate data-driven narratives effectively.

What's included

19 videos7 readings1 quiz1 discussion prompt

In this module, you will explore the powerful combination of Plotly, Dash, and Streamlit for creating interactive and dynamic visualizations within a dashboard. You will use Plotly to create visually appealing histograms, scatterplots, and line plots that can be embedded within a dashboard. You will also dive into Dash and Streamlit, two popular Python frameworks for building interactive web-based dashboards. By the end of the week, you will be able to apply your knowledge and create a comprehensive dashboard that incorporates these visualizations, enabling users to explore and interact with your data.

What's included

15 videos6 readings1 quiz1 discussion prompt

In this module, you will dive into two cloud-based tools, Tableau and Amazon QuickSight, to create compelling visualizations, and gain insights from your data in a user-friendly and interactive manner. You will first use Tableau to design and create histograms, scatterplots, and line plots that effectively showcase your data. You will then use Amazon QuickSight, an intuitive and cloud-based business intelligence tool, to create visually appealing and interactive visualizations. By the end of the week, you will be able to apply your knowledge and create captivating visualizations using these platforms.

What's included

14 videos5 readings1 quiz1 discussion prompt

Instructors

Matt Harrison
Duke University
3 Courses8,700 learners

Offered by

Duke University

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