Data Visualization Mastery

Data Visualizations play a key role in helping companies make data driven decisions. This Skillsoft Aspire journey will help you understand the significance of creating user-centered visuals, best practices to follow along with various types of charts, plots, graphs and diagrams to represent data visually. Along with eye catching visualizations using Excel from various imported data formats, you will also learn to create various types of visualizations using BI tools like QlikView. You will then explore creating interactive dashboards and infographics for your visualization projects. You will also explore various techniques for creating visualizations using various Python libraries like Matplotlib, Plotly, and Bokeh before modeling the data.

This learning path, with more than 43 hours of online content, is divided into the following four tracks:
• Track 1: Data Visualization with Excel
• Track 2: Data Visualization with Bi Tools
• Track 3: Creating Infographics for Data Visualizations
• Track 4: Data Visualization with Python

Track 1: Data Visualization with Excel
In this track, the focus will be on data visualization best practices and data visualization using Microsoft Excel.

Content:
E-learning courses
• Data Visualization: Best Practices for Creating Visuals
• Excel Visualization: Getting Started with Excel for Data Visualization
• Excel Visualization: Building Column Charts, Bar Charts, & Histograms
• Excel Visualization: Visualizing Data Using Line Charts & Area Charts
• Excel Visualization: Building Box Plots, Sunburst Plots, Gantt Charts, & More
• Excel Visualization: Plotting Stock Charts, Radar Charts, Treemaps, & Donuts

Online Mentor
• You can reach your Mentor by entering chats or submitting an email.
Final Exam assessment
• Estimated duration: 90 minutes

Track 2: Data Visualization with BI Tools
In this track, the focus will be on data visualization using QlikView.

Content:
E-learning courses
• QlikView: Getting Started with QlikView for Data Visualization
• QlikView: Creating Line Charts, Combo Charts, Pivot Tables, & Block Charts
• QlikView: Creating Mekko Charts, Radar Charts, Gauge Charts, & Scatter Charts

Online Mentor
• You can reach your Mentor by entering chats or submitting an email.

Final Exam assessment
• Estimated duration: 90 minutes

Practice Labs: Data Visualization with Excel and BI Tools (estimated duration: 8 hours)

• Perform data visualization tasks with Excel such as creating and customizing line, bar, area and band charts. Then use QlikView to create tables and bar, combo, line and funnel charts. This lab provides access to tools typically used for data visualization, including:
o Microsoft Excel 2019
o QlikView 12

Track 3: Creating Infographics for Data Visualizations
In this track, the focus will be on creating infographics with Infogram and Visme.

Content:
E-learning collections
• Infogram: Getting Started
• Infogram: Advanced Features
• Visme: Introduction
• Visme: Exploring Charts
• Visme: Designing a Presentation

Online Mentor
• You can reach your Mentor by entering chats or submitting an email.
Final Exam assessment
• Estimated duration: 90 minutes

Track 4: Data Visualization with Python
In this track, the focus will be on data visualization with Python using Matplotlib, Bokey, and Plotly.

Content:
E-learning collections
• Python & Matplotlib: Getting Started with Matplotlib for Data Visualization
• Python & Matplotlib: Creating Box Plots, Scatter Plots, Heatmaps, & Pie Charts
• Data Visualization: Building Interactive Visualizations with Bokeh
• Data Visualization: More Specialized Visualizations in Bokeh
• Data Visualization: Getting Started with Plotly
• Data Visualization: Visualizing Data Using Advanced Charts in Plotly

Online Mentor
• You can reach your Mentor by entering chats or submitting an email.

Final Exam assessment
• Estimated duration: 90 minutes

Practice Labs: Creating Infographics and Data Visualization with Python (estimated duration: 8 hours)
• Perform data visualization tasks such as creating an Infogram project, building an infographic and creating box-and-wisker plots, line charts and histograms. Then visualize relationships using a scatter plot, create a bar chart using Bokeh, and create a box chart using Plotly. This lab provides access to tools typically used for data visualization, including:
o Jupyter Notebook
o matplotlib
o numpy
o pandas
o Plotly
o Bokehh

ADDITIONAL INFORMATION