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Python for Data Visualization
Course
Python for Data Visualization
Get started with Python and build essential skills for data visualization in just 5 weeks. No prior programming experience required.
Flexible Schedule
Intermediate Level
Mentor Support
Estimated Time
5 weeks
Data visualization is one of the top five skills required for data science (Harvard Business School). Aspiring data professionals, data analysts, and data scientists proficient in data visualization are in ihigh demand. This course gives you the data visualization skills and practical experience you need to catch an employer's eye in just 5 weeks.
During this course, youll learn how to tell compelling stories through data visualization and transform raw data into meaningful insights. Youll learn to use various Python tools and libraries, such as Matplotlib, Seaborn, Folium, Plotly, and Dash. Youll also master how to analyze and present complex data in an accessible and engaging way, use basic and advanced plotting techniques, and create interactive dashboards.
Additionally, youll gain valuable practical experience working on hands-on labs and a final project to analyze historical automobile sales data, visualize it, and then communicate your findings. Great experience to talk about in interviews!
If you want to build in-demand data visualization skills and enhance your data analytics job opportunities, enroll today!
This course comprises five purposely designed modules that take you on a carefully defined learning journey.
It is a self-paced course, which means it is not run to a fixed schedule with regard to completing modules. It is anticipated that you will complete the course in 5 weeks. However, as long as the course is completed by the end of your enrollment, you can work at your own pace. And dont worry, youre not alone! You will be encouraged to stay connected with your learning community through the course discussion space.
The materials for each module are accessible from the start of the course and will remain available for the duration of your enrollment. Methods of learning and assessment will include discussion space, videos, reading material, quizzes, hands-on labs, quizzes and final assignment.
Once you have successfully completed the course, you will earn your IBM Certificate.
You will be able to:
- Implement data visualization techniques and plots using Python libraries, such as Matplotlib, Seaborn, and Folium, to tell a stimulating story.
- Create different types of charts and plots such as line, area, histograms, bar, pie, box, scatter, and bubble.
- Create advanced visualizations such as waffle charts, word clouds, regression plots, maps with markers, and choropleth maps.
- Generate interactive dashboards containing scatter, line, bar, bubble, pie, and sunburst charts using the Dash framework and Plotly library.
- Beginners in programming
- Aspiring data analysts & data scientists
- No prior programming experience required.
Course Outline
General Information
Course Learning Objectives
Video: Welcome to the Course (3:48)
How to Make the Most of this Course
Syllabus
Grading Scheme
Module Introduction and Learning Objectives
Video: Overview of Data Visualization (07:22)
Video: Types of Plots (8:10)
Video: Plot Libraries (6:24)
Video: Introduction to Matplotlib (6:40)
Video: Basic Plotting with Matplotlib (4:41)
Video: Dataset on Immigration to Canada (03:14)
Video: Data Visualization with Python: Line Plots (4:03)
App Item: Lab: Exploring and Pre-processing a Dataset using Pandas
App Item: Lab: Introduction to Matplotlib and Line Plots
Practice Quiz: Introduction to Data Visualization
Reading: Summary: Introduction to Data Visualization Tools
Cheat Sheet: Data Preprocessing Tasks in Pandas & Plot Libraries
Quiz: Graded Quiz: Introduction to Data Visualization Tools (10 Questions)
Module Introduction and Learning Objectives
Video: Area Plots (5:27)
Video: Histograms (4:58)
Video: Bar Charts (3:29)
Lab: Area Plots, Histograms, and Bar Charts
Practice Quiz: Basic Visualization Tools
Video: Pie Charts (3:29)
Video: Box Plots (3:04)
Video: Scatter Plots (3:44)
Lab: Pie Charts, Box Plots, Scatter Plots, and Bubble Plots
Video: Plotting Directly with Matplotlib (8:28)
Lab: Plotting Directly with Matplotlib
Practice Quiz: Specialized Visualization Tools
Summary: Basic and Specialized Visualization Tools
Cheat Sheet: Plotting with Matplotlib using Pandas
Graded Quiz: Basic and Specialized Visualization Tools (10 Questions)
Module Introduction and Learning Objectives
Video: Waffle Charts & Word Cloud (5:12)
Video: Seaborn and Regression Plots (4:29)
Lab: Waffle Charts, Word Clouds, and Regression Plots
Practice Quiz: Advanced Visualization Tools
Video: Introduction to Folium (2:54), Incomplete3 min3 minutes
Video: Maps with Markers (5:24)
Video: Choropleth Maps (4:23)
Lab: Creating Maps and Visualizing Geospatial Data
Practice Quiz: Visualizing Geospatial Data
Reading: Summary: Advanced Visualizations and Geospatial Data
Cheat Sheet: Maps, Waffles, WordCloud and Seaborn
Graded Quiz: Advanced Visualizations and Geospatial Data (10 Questions)
Module Introduction and Learning Objectives
Video: Dashboarding Overview (4:33)
Reading: Additional Resources for Dashboards
Video: Introduction to Plotly (5:43)
Reading: Additional Resources for Plotly
App Item: Plotly Basics: Scatter, Line, Bar, Bubble, Histogram, Pie, Sunburst
Practice Quiz: Creating Dashboards with Plotly
Video: Introduction to Dash (3:44)
Overview of Cloud IDE Lab Environment
App Item: Dash Basics: HTML and Core Components
Reading: Additional Resources for Dash
Video: Make Dashboards Interactive (5:47)
Reading: Additional Resources for Interactive Dashboards
App Item: Add Interactivity: User Input and Callbacks
Video: Walkthrough the Flight Delay Time Statistics Dashboard Lab (7:54)
App Item: Flight Delay Time Statistics Dashboard
Practice Quiz: Working with Dash
Reading: Summary: Creating Dashboards with Plotly and Dash
Cheat Sheet: Plotly and Dash
Graded Quiz: Creating Dashboards with Plotly and Dash (10 Questions)
Module Introduction and Learning Objectives
Practice Project Overview
Practice Assignment: Part 1 - Analyzing wildfire activities in Australia
Practice Assignment: Part 2 - Creating Dashboards
Final Project Overview
Final Assignment: Part 1 - Create Visualizations using Matplotlib, Seaborn & Folium
Final Assignment: Part 2 - Create Dashboard with Plotly and Dash
Peer Graded Review: Final Assignment: Part 3 - Submission and Grading (1 Question)
Final Assignment
Final Exam: Data Visualization with Python (15 Questions)
Why Learn with SkillUp Online?
We believe every learner is an individual and every course is an opportunity to build job-ready skills. Through our human-centered approach to learning, we will empower you to fulfil your professional and personal goals and enjoy career success.
Reskilling into tech? We’ll support you.
Upskilling for promotion? We’ll help you.
Cross-skilling for your career? We’ll guide you.
Personalized Mentoring & Support
1-on-1 mentoring, live classes, webinars, weekly feedback, peer discussion, and much more.
Practical Experience
Hands-on labs and projects tackling real-world challenges. Great for your resumé and LinkedIn profile.
Best-in-Class Course Content
Designed by the industry for the industry so you can build job-ready skills.
Job-Ready Skills Focus
Competency building and global certifications employers are actively looking for.
FAQs
Data visualization is the process of representing data in graphical or visual formats to make insights easier to understand and communicate.
Python provides libraries such as Matplotlib, Seaborn, Plotly, Dash, and Folium that allow you to create charts, plots, interactive dashboards, and geospatial maps to effectively communicate data insights.
Python is widely used for data visualization due to its powerful libraries, simplicity, and ability to integrate with data analysis workflows.
Yes, this Python Data Visualization course is an online, hands-on learning experience where you can practice creating visualizations and dashboards at your own pace.
This course is designed to be completed in 5 weeks, providing practical experience with Python visualization tools and real-world datasets.
You will learn to create basic and advanced charts, analyze and visualize datasets, build interactive dashboards, work with geospatial maps, and tell data-driven stories using Python.
This Python for Data Visualization course is part of the bigger program named IBM Data Analyst Professional Certificate. The course aims to give you industry-recognized skills in data visualization with Python.
Youll cover line charts, area plots, bar charts, pie charts, histograms, scatter plots, box plots, waffle charts, word clouds, regression plots, and geospatial mapping using Folium, along with building interactive dashboards using Plotly and Dash.
Yes, upon completion, you will receive an IBM Certificate that you can share on LinkedIn and include in your professional portfolio.
Data visualization specialists and analysts with Python skills typically earn competitive salaries, which increase with experience, industry, and location.
Proficiency in data visualization with Python enhances your ability to communicate insights, making you more attractive to employers in data analytics, business intelligence, and data science roles.
Industries including finance, healthcare, marketing, e-commerce, consulting, and technology actively seek professionals skilled in Python data visualization.
You can pursue roles such as data analyst, business intelligence analyst, data scientist, reporting analyst, or visualization specialist.
Yes, data visualization is a highly sought-after skill, essential for turning complex data into actionable insights.
By completing hands-on labs, a real-world project on automobile sales data, and building interactive dashboards, you gain practical experience that can be showcased in interviews and portfolios.
Type of certificate
IBM Certificate
About this course
05 Modules
05 Skills
Includes
Discussion space
11 Hands-on labs
07 Practice quizzes
04 Graded quizzes
01 Final exam
01 Final project
Create
Maps and Visualizing Geospatial Data
Dashboards with Plotly
Exercises to explore
Data Visualization Tools
Plotly and Dash
This course has been created by
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