What You’ll Learn
This Storytelling Through Data Visualization course will teach you how to draw out the story that lies buried in your dataset. Going beyond simple graphs, you’ll learn how to use the Seaborn data visualization library to create outstanding and insightful visualizations.
You’ll discover how the use of color, “data-ink” ratio, and data layout impact your presentations. We’ll even give you tips on how and when to annotate your visualizations, along with other tricks to help you master the art of data visualization.
Enroll in this course if you want to do the following:
- Improve the look of your graphs
- Leverage common data visualization techniques
- Use color to your advantage and learn other best practices
- Uncover the data-ink ratio for plots
- Learn the importance of your data layout
- Provide additional context for data visualization using annotations
- Practice your data presentation skills and master the art of the chart
- Export your data using matplotlib
- Learn about the Seaborn data visualization library
- Tackle the challenges of visualizing geographic data like latitude/longitude
- Display geographic data on a world map
How Our Storytelling Through Data Visualization Course Works
Data visualization is an invaluable skill in data science, especially for data analysts and data scientists. Not everyone can intuitively understand the insights contained in a dataset, which is why data visualization is so ubiquitous and necessary. We want to see you flourish in a data science career, so we’ve made this data visualization course to help you get there. This particular course is for intermediate Python users and it builds upon the essentials covered in our previous Python visualization lessons.
Here at Dataquest, it’s our mission to help you level up your data science career skills. That’s why we believe in learning by doing. With us, you’ll never have to sit through boring “training” videos or ineffective memorization exercises. With Dataquest, you’ll acquire, refine, and retain in-demand data visualization skills by solving real problems with real code starting on day one!
In this Storytelling Through Data Visualization course, you’ll learn quickly and efficiently by completing our hands-on, interactive lessons, practice problems, and guided projects. You’ll be digging into real-world datasets and visualizing insights from the Department of Education. Here, you’ll learn the unique challenges of plotting geographical data using a public flight dataset.
One of the biggest perks of learning with Dataquest is the ability to build a compelling project portfolio. We know that one of the first and most important things hiring managers and employers look for in a candidate is a portfolio that demonstrates the skills for the job. That’s why all of our courses culminate in a portfolio project! Our projects challenge you to synthesize and implement your new skills in solving real-world problems.
Additionally, with Dataquest, you’ll join our thriving and supportive community of data students and professionals. That way, you’ll never learn alone! And if you ever need extra help, our powerful and responsive support tools are just a click away.
Here’s a glance at our Storytelling Through Data Visualization course:
- This course is the sixth in the Data Analyst in Python Career Path. It consists of the five lessons listed below, which cover in-depth programming concepts in Python.
- You’ll write real code with dozens of practice problems so you can apply your skills.
- At the end of each course, you’ll complete a guided project to reinforce your new knowledge and expand your portfolio.
- When you complete this course, you’ll receive a certificate that you can share with your professional network.
- Once you complete this course, you’ll be ready for more advanced Python courses.
- Engage with our friendly community of data professionals, get feedback on your projects, and keep building your skills.
Enroll in this course to learn Storytelling Through Data Visualization!
Storytelling Through Data Visualization Lessons List
Who Is This Storytelling Through Data Visualization Course For?
This course was designed for intermediate Python users who already have a firm grasp of the basics of Python programming and data visualization. Whether you’re a data science newbie looking to expand your knowledge or a seasoned data scientist who wants to brush up on the basics, this course is for you!
We’ve designed this data visualization course to help as many people as possible:
- Data science beginners looking for fundamental data visualization knowledge
- Python users seeking a deeper understanding of the inner workings of Python
- People who want a career as a data analyst or data scientist
- People seeking remote work
- Anyone who works with data in telecommunication, finance, education, and healthcare
- Junior data scientists or data analysts who want to advance in their current positions
- Anyone who wants to be able to capture, process, and interpret data
- Students who want to develop a competitive portfolio
- Experienced Python users who want to fill in the blanks and brush up on the basics
Students Who Enrolled in This Course Also Enrolled in These:
If you’re learning data visualization skills to pursue a career in data analysis, we recommend that you enroll in the following paths. We’ve designed them to give you the skills and knowledge you need to get hired faster!
If you already have a background in data analysis and simply want to expand your skill set, we’re happy to recommend the following courses:
Qualify for In-demand Jobs in Data Visualization
Python is one of the world’s leading programming languages, and learning to use Python libraries like Seaborn for data visualization can be an extremely valuable skill to add to your repertoire.
By completing this course, you’ll develop in-demand data science career skills that will prepare you to enter any of the following positions in a variety of industries:
- Data analyst
- Data scientist
- Python developer
- Junior Data scientist
- Business analyst
- Machine learning scientist
- Financial analyst
- Software developer
- Machine learning engineer
- GIS analyst
- Biotech analyst
- Data collection analyst
- Python full stack developer