About the course
Turn complex data into meaningful visualization to gain insights by creating perfect charts and histograms
A lot of us who work with data know how to make charts, but don't know how to make effective visualizations that send a clear, efficient, and truthful message. Many of us don't realize what makes charts speak and how to remove noise and focus only on what's important.
This course takes a different approach, focusing instead on various data science tools, typical workflows in data projects, algorithms, and the math behind data science. You will work on presenting and communicating with data using visual media such as charts, plots, and histograms with real-world datasets.
By working with the four most popular chart types, you will dissect each of them at a microscopic level while using interesting real-world datasets with practical examples in Excel. The aim of the course is to show you where charts work and where they don't and what makes these charts easier to understand.
By the end of the course, you will have learned how to implement the principles of effective visual communication using Excel.
The code bundle for this video course is available at- https://github.com/PacktPublishing/Perfect-Excel-Charts
Style and Approach
This course adopts a top-down approach where you will learn the most popular data visualization techniques. You will be walked through real-world datasets to show how you can get insights visually from a huge amount of data.
What You Will Learn
- Apply a top-down approach in data analysis by starting with high-level questions, sketches, and metric definitions for more effective communication with data.
- Work with real-life noisy data and communicate findings that are relatable to real life with clarity and truthfulness
- Dissect common elements of an ideal chart to get an understanding of how to use it to tell a clear story
- Discover how elements of each chart type serve to add clarity and substance to the chart message
- Build perfect charts using Excel, one of the most popular statistical applications used worldwide
Nikita Barsukov is a software developer and data scientist with 10 years' experience in the industry. He is a self-taught data scientist, who learned early on that it is often messaging, insight and data storytelling that is important in data science, not technology or software. He went through a traditional data science path at the beginning of his career—for example, learning R and machine learning algorithms using online courses. Then he also quickly grasped the value in visual data storytelling, using charts as a mode to communicate and tell something. He lives in Copenhagen, Denmark with his beautiful wife and three awesome sons.
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