32 Data Visualization Strategies - Basic Theory & Practice for Non-Majors

We explain 32 data visualization techniques very quickly and easily from a non-expert's perspective!

(4.5) 12 reviews

222 learners

Level Beginner

Course period Unlimited

Data literacy
Data literacy
AI
AI
Python
Python
Chart Analysis
Chart Analysis
Business Productivity
Business Productivity
Data literacy
Data literacy
AI
AI
Python
Python
Chart Analysis
Chart Analysis
Business Productivity
Business Productivity

Reviews from Early Learners

4.5

5.0

Yu

33% enrolled

I like that you explain difficult concepts in an easy-to-understand way.

5.0

서성훈

63% enrolled

This is a lecture that helps you reach a new level of understanding in data analysis.

5.0

경철

100% enrolled

This was very helpful. The applications of AI are truly endless.

What you will gain after the course

  • I can understand why I need data visualization.

  • You can develop insights to look at data and build persuasiveness.

  • You can analyze data with just a click!

A data visualization course served up directly by an AI engineer!

Follow these 32 core examples, and you'll become a data visualization expert too! 😃

A best-selling author who has written many books and


An instructor who has gathered over 1,900 students on Inflearn alone, and


An expert so recognized that EBS even scheduled a 6-part special lecture series.


"The ability to explain technology easily" alone

I am an expert who has conducted over 300 invited lectures.


I am confident that I will definitely satisfy you!


"A lecture planned at the request of a global major corporation"


I received a request for a special lecture on data visualization from a well-known foreign company.

While I was working hard to prepare the lecture, this thought occurred to me.


"If I re-process this to be a bit easier, wouldn't it be helpful for everyone?"


Therefore, this is a lecture filmed with a significantly lower difficulty level and additional hands-on practice.


A lecture taken by employees of the No. 1 European company in the XX field,

Listen from the comfort of your own home!


After learning data visualization...

You will develop an eye for data

By looking at various visualization techniques at a glance and following the hands-on exercises, you will develop the insight to determine which data should be analyzed and in what way.

Strategies for persuasion will come to mind

The very reason for data visualization's existence is to ensure persuasiveness. Do you want the ability to persuade colleagues and superiors with data-driven materials?

You don't need to know statistical knowledge or coding

It is enough to just watch the videos comfortably, as if you were watching Netflix.

Understand the world in higher resolution!

You see as much as you know. As you navigate the sea of data, you will begin to see things you have never seen before!

Here is what you will learn

Why should we learn data visualization?

  • In the AI era, why should we learn data visualization?

  • How to easily visualize data

  • Wait, I can do this too!

Incredibly easy basic theory

  • Strategies for choosing data visualization techniques

  • Dimensions of data

  • Methods for reducing the dimensions of data

A practice so easy it's almost anticlimactic

  • Do what's possible in Excel, in Excel!

  • With professional and clean Gemini vibe coding!

  • Creating a click-and-go visualization tool in the form of a web app!

  • I'll also show you how to visualize using Python!

Visualization strategies for 1D data

  • Histogram

  • KDE Plot

  • Strip Plot

  • Box Plot

  • Swarm Plot

  • Violin Plot

  • ECDF

Visualization strategies for 2D data

  • Scatter Plot

  • Regression

  • Waterfall Chart

  • Line Chart

  • Slope Chart

  • 2D Density Plot

  • Hexabin Plot

  • Heat Map

  • Residual Plot

Visualization Strategies for High-Dimensional Data

  • Clustering

  • K-means Clustering

  • Clustered Heat Map

  • PCA

  • NMF

  • t-SNE

  • UMAP

  • WordCloud

  • Sankey Chart

  • Radial Tree

  • Radial Tidy Tree

Notes before taking the course

Learning Materials

  • Provides all practice data and analysis web apps introduced in the video

Recommended for
these people

Who is this course right for?

  • Those who are curious about strategies for being persuasive based on data

  • Marketers and planners who want to easily gain insights from fragmented data

  • Someone who handles data frequently

Need to know before starting?

  • It's okay even if you don't have it!

Hello
This is bhban

Career Verified

2,404

Learners

192

Reviews

29

Answers

4.7

Rating

7

Courses

Current) CEO of NaNa Lab

Former) CTO/Director of Sangsangteotbat Co., Ltd.

KAIST B.S. and M.S. (Early Graduation) in Bio and Brain Engineering

Andong Gyeongan High School (Early Graduation)

Published over 90 books, papers, and patents

https://bhban.kr

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Curriculum

All

27 lectures ∙ (3hr 32min)

Course Materials:

Lecture resources
Published: 
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Reviews

All

12 reviews

4.5

12 reviews

  • 08zbfl3006님의 프로필 이미지
    08zbfl3006

    Reviews 5

    Average Rating 5.0

    5

    33% enrolled

    I like that you explain difficult concepts in an easy-to-understand way.

    • kcpark828320님의 프로필 이미지
      kcpark828320

      Reviews 1

      Average Rating 5.0

      5

      100% enrolled

      This was very helpful. The applications of AI are truly endless.

      • n03372419866hoon2381님의 프로필 이미지
        n03372419866hoon2381

        Reviews 1

        Average Rating 5.0

        5

        63% enrolled

        This is a lecture that helps you reach a new level of understanding in data analysis.

        • n03372387699jeon5210님의 프로필 이미지
          n03372387699jeon5210

          Reviews 2

          Average Rating 5.0

          5

          100% enrolled

          It was a useful lecture for those who work with big data.

          • hschoi286287님의 프로필 이미지
            hschoi286287

            Reviews 2

            Average Rating 5.0

            5

            33% enrolled

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