Mastering Data Visualization Track - Online Learning with Certificate

Mastering Data Visualization

Intermediate

4.4

9 reviews

25 Learners

Updated 05/2025

This track helps master key data visualization techniques. It covers NumPy and Pandas for data preparation and processing, Python libraries for creati…

150

Chapters

Learning hours

146

Assignments

AI Assistant

Shareable Certificate

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What you will learn

Creating and manipulating NumPy arrays

Performing math operations with NumPy

Visualizing data with Matplotlib

Indexing and slicing NumPy arrays

Creating and manipulating pandas DataFrames

Building interactive reports in Power BI

Applying common NumPy functions

Handling missing values in pandas

Creating dynamic visualizations in Tableau

Learning track content

Explore the applications of NumPy and understand why it's one of the most popular libraries for numerical computing. Learn the different ways to create and initialize arrays to handle various data needs efficiently.

Introduction to NumPy

Basic Array Creation

Creating Higher Dimensional Arrays

Creation Functions for 1D Arrays

Creation Functions for 2D Arrays

General Array Creation Functions

Random Arrays

Discover how to access specific elements and subsets in NumPy arrays using index notation. Learn to apply conditional indexing to filter data and manage missing values efficiently.

Basic Indexing

Multidimensional Indexing

Slicing

Slicing in 2D Arrays

Integer Array Indexing

Boolean Indexing

More about Comparisons

Boolean Indexing in 2D Arrays

Assigning Values to Indexed Elements

Assigning Values to Indexed Subarrays

NumPy provides many built-in functions for performing common array operations. Learn how to apply these tools to transform, aggregate, and analyze data efficiently without writing repetitive code.

Learn how to perform mathematical operations efficiently on NumPy arrays. Apply these operations to solve real-world problems and gain a deeper understanding of how vectorized computations speed up numerical analysis.

Broadcasting

Basic Mathematical Operations

Basic Linear Algebra

Dive into the fundamentals of the pandas library. Learn to create and manipulate Series and DataFrames, explore their structure, and build confidence in performing essential data operations.

What Is pandas?

Series

Challenge: Creating a Series

DataFrame

Quiz: Creating a Series

Quiz: Creating a DataFrame

Adding a New Column

Inserting a New Column

Deleting a Row/Column

Quiz: Matching the Functions

Working with Columns

Quiz: Extracting Columns

iloc[] Basics

Challenge: Using iloc[]

Master how to load and manage data from CSV and TXT files. Gain practical experience importing datasets and preparing them for further analysis using pandas tools.

CSV Files

TXT Files

Quiz: Working with Files

Quiz: Accessing the Columns

Learn to explore, clean, and summarize data effectively. Understand how to handle missing values, extract insights, and perform basic statistical operations with pandas.

Viewing the Data

Quiz: Using head()

Quiz: head(), tail(), and sample()

Exploring the Dataset

Column Names and Data Types

Finding Null Values

Quiz: Identifying Null Values

Challenge: Dropping Null Values

Challenge: Filling Null Values

Quiz: Null Values

Describing the Data

max() and min()

Quiz: Statistical Operations

sum() and count()

Unique Values

Discover the essentials of data visualization with Matplotlib. Learn its core concepts, explore its advantages, and create your first simple plot using this fundamental plotting library.

Plotting Applications

Why Matplotlib Matters?

Creating a Canvas

Basic Plotting

Master how to visualize data through the most popular plot types. Learn to build line, scatter, and bar charts to clearly communicate insights from your data.

Learn to make your plots more informative and visually appealing. Add titles, legends, colors, and grids, and discover how to arrange multiple subplots effectively.

Adding Title to the Plot

Adding Legend

Axes Customization

Colors and Transparency

Customizing Grid

Subplots

Explore statistical visualizations that help analyze data distributions and patterns. Create histograms, box plots, and pie charts to uncover deeper statistical insights.

Histogram

Box Plot

Pie Chart

Take your visualization skills to the next level with Seaborn. Create advanced plots like countplots, KDEs, pair plots, and heatmaps while mastering Seaborn’s elegant style and customization options.

Dive into the world of Power BI and build a solid foundation. You'll cover everything from installation and setup to connecting data sources and creating your first report.

What is Power BI?

Installation and Setup

Overview of Power BI

Connecting to Data Sources

Basics of Power Query

Creating Your First Report

Explore essential data preparation techniques, including cleaning, transforming, and combining multiple data sources. You'll also tackle handling missing values, data profiling, and various data manipulation methods.

Data Cleaning and Transformation

Data Profiling and Exploration

Handling Missing Values

Creating Columns

Handling Multiple Data Sources

Appending and Merging Data

Pivoting Data

Master the fundamentals of data modeling, from understanding data models and creating relationships to getting the hang of DAX basics. You'll also learn to create measures and calculated columns.

Introduction to Data Models

Creating Relationships

DAX (Data Analysis Expressions) Basics

Measures, Quick Measures, and Calculated Columns

Discover various visualization techniques and customize visuals for better insights. You'll also explore advanced features like slicers, filters, and drill-down/drill-through capabilities to enhance your data analysis.

Creating Visualizations

Map and Tool Tips

Slicers and Filters

Drilldown and Hierarchies

Boost the usability and storytelling power of your reports by using themes, configuring report pages, and leveraging advanced features like the Analyze feature and identifying outliers. You'll also create groups, bins, and clusters for deeper insights.

Using Themes

Configuring Report Page

Using Shapes and Buttons

Creating Groups and Bins

Analyzing Features

Finding Anomalies

This section lays the groundwork for mastering Tableau by guiding you through installation, navigation, and foundational operations. From performing joins and splitting columns to understanding filters, marks, and the data pane, you will be equipped with essential tools for data exploration and visualization.

What You Will Learn

Tableau Installation

First Steps

Field Operations and Joins

Challenge: Joining Tables and Splitting Columns

Exploring the Data Pane

Challenge: Identifying Top Performers by Profit

Pages, Filters, and Marks Overview

Challenge: Finding the Sub-Category with the Lowest Sales

This section delves into Tableau's powerful tools for data organization, filtering, and customization. You'll learn to differentiate dimensions and measures, work with continuous and discrete fields, and create calculated fields and interactive dashboards. Through practical challenges, you'll apply these tools to analyze data, uncover insights, and enhance your visualizations.

Dimensions and Measures

Challenge: Comparing Sales and Profit by State

Continuous and Discrete Fields

Challenge: Identifying the Month with Lowest Sales

Dimension Filters

Measure Filters

Challenge: Finding the Most Profitable Customer in Art

Calculated Fields

Challenge: Comparing California and New York to Other States

Interactive Dashboards with Parameters

Challenge: Finding the Sub-Category with the Most Sales

Working with Sets

Challenge: Analyzing Bookcase Profit Concentration

Sets Applications

This section focuses on creating impactful visualizations to uncover patterns and trends in your data. From heatmaps and scatter plots to treemaps and combination charts, you'll explore a variety of chart types tailored to different analytical needs.

Visualizing Data with Heatmaps

Challenge: Identifying Top-Selling Sub-Category by Region

Scatter Plots

Challenge: Determining the Highest Sales and Profit by State

Treemaps

Challenge: Analyzing the Least Profitable Sub-Category

Combination Charts

Challenge: Comparing Sales and Profit Trends for Phones

Sparklines

This section introduces advanced visualization techniques to enhance data analysis and storytelling. You'll learn to create bullet graphs, stacked area charts, histograms, and box plots, enabling deeper insights into trends, distributions, and comparisons.

Bullet Graphs

Challenge: Analyzing Profit Changes Between 2016 and 2017

Stacked Area Charts

Challenge: Identifying the Region with the Highest Profit

Histograms

Box Plots

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