
Learn how to choose the right visualization by matching data types, categorical or numerical, to charts like bar, pie, scatterplot, line chart, and time series, using practical frameworks.
Learn how color theory and color perception affect data visualization, and apply two-color palettes with a three-color upper limit to emphasize information and enhance chart readability.
Explore bar charts through general theory and a car-brand dataset. Practice building and styling bar charts using a two-column dataset of car brands and ad counts to visualize information clearly.
Learn when to use pie charts, avoid common misuses like non-summing data and 3d pie charts, limit categories, and consider line charts for timelines.
Learn how area charts, including stacked and 100 percent stacked area charts, reveal trends across variables over time. Analyze a car engine type dataset (diesel, petrol, gas, other) from 1982–2016.
Explore scatter plots and regression analysis to quantify relationships between variables, using a regression line to illustrate linear fits and the relation between advertising budget and sales across markets.
Interpret a bar and line combination chart showing yearly participants and Python usage, while noting data nuances and the dos and don'ts of chart design.
Master combination charts by ensuring compatibility when stacking, using data from the same source, labeling clearly, and choosing dual y-axes only when necessary.
Do you wish you had superior data interpretation skills?
Does your workplace require data visualization proficiency?
Do you wish to learn about a rich variety of graphs and charts?
If you answered “yes” to any of these questions, this is the course for you.
Data visualization is the face of data. Many people look at the data and see nothing. The reason for that is that they are not creating good visualizations. Or even worse – they are creating nice graphs but cannot interpret them accurately.
That’s why we’ve created the ‘Introduction to Data Visualization Course’. To help you better understand and interpret different types of charts:
Graphs and charts included in the Complete Data Visualization Course:
· Bar chart
· Pie chart
· Stacked area chart
· Line chart
· Histogram
· Scatter plot
· Scatter plot with a trendline (regression plot)
We live in the age of data. And being able to gather good data, preprocess it, and model it is crucial.
However, there is nothing more important than being able to interpret that data. And data visualization allows us to achieve just that. At the end of the day, data charts are what conveys the most information in the shortest amount of time. And nothing speaks better than a well-crafted and meaningful data visualization.
The skills you acquire during the course will help you develop an analytical approach when creating any type of chart based on the data you’re given.
At the same time, you’ll be able to interpret charts in general, so you’ll be on top of your game whenever you’re examining someone else’s work. You’ll be able to gain insight from a chart in a short amount of time, as well as spot if something is wrong or missing from a visualization.
Why do you need these skills?
1. Salary/Income – careers in the field of data science are some of the most popular in the corporate world today. Literally every company nowadays needs to visualize their data, therefore the data viz position is very well paid
2. Promotions – being the person who creates the data visualizations makes you the bridge between the data and the decision-makers; all stakeholders in the company will value your input, ensuring your spot on the strategy team
3. Secure future –understanding data in today’s world is the most important skill to possess and it is only developed by seeing, visualizing and interpreting many datasets
Please bear in mind that the course comes with Udemy’s 30-day money-back guarantee. And why not give such a guarantee? We are certain this course will provide a ton of value for you.
Let's start learning together now!