In today's data-driven world, the ability to create compelling visualizations and tell impactful stories with data is a crucial skill. This comprehensive course will guide you through the process of visualization using coding tools with Python, spreadsheets, and BI (Business Intelligence) tooling. Whether you are a data analyst, a business professional, or an aspiring data storyteller, this course will provide you with the knowledge and best practices to excel in the art of visual storytelling.
Data Visualization with Python
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Data Visualization with Python
This course is part of Applied Python Data Engineering Specialization
Instructors: Matt Harrison
2,957 already enrolled
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4.2
(15 reviews)
Intermediate level
Recommended experience
9 hours to complete
3 weeks at 3 hours a week
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.
Skills you'll gain
Details to know
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Assessments
4 assignments
Taught in English
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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.
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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 assignment2 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 assignment1 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 assignment1 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 assignment1 discussion prompt
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Reviewed on Aug 28, 2024
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