ANA5004X - Data Visualization with Matplotlib and Seaborn
Course Description
In a world overflowing with data, the ability to communicate insights clearly and effectively is what sets professionals apart. Data Visualization with Matplotlib and Seaborn is an essential course for aspiring data analysts, business intelligence professionals, and anyone eager to master the art of storytelling with data.
This course introduces you to the fundamentals of data visualization, exploring why visualizing data is a critical skill in today’s data-driven workplace. You'll gain hands-on experience with Matplotlib, the foundational Python library for creating line plots, bar charts, histograms, and more. Then, you’ll dive into Seaborn, a powerful tool for crafting advanced visualizations like heatmaps, pair plots, and distribution charts that uncover deeper trends and patterns.
Whether you're preparing for a career in data analytics, data science, or business intelligence, this course helps you build the visualization skills employers expect. Perfect for learners aiming to stand out in entry-level data roles, this training provides the tools to transform raw data into meaningful, visual narratives.
Key Benefits
- 100% online self-paced course
- Learn entry-level job skills for a career in data analytics
- No prior experience required.
- No textbooks and other materials required for purchase.
Learning Modules Include
- Unit 1 - Introduction to data visualization and its importance.
- Unit 2 - Plotting with Matplotlib (line plots, bar charts, histograms, etc.).
- Unit 3 - Advanced visualizations with Seaborn (heatmaps, pair plots, etc.).
- Unit 4 - Customizing and styling plots.
Course Learning Outcomes
- Create and interpret various types of data visualizations using Matplotlib and Seaborn.
- Understand the principles of effective data visualization.
- Customize visualizations to convey insights clearly and effectively.
Requirements to Enroll
No application is needed to enroll. All learners are eligible to enroll in the course. There are no admission requirements. It is recommended that learners have a high school diploma or GED, and have basic computer and internet knowledge.
Estimated Time to Completion
This course can be completed in 20 hours
Access Time
Learners will have access to their course learning modules for up to 12 months from the date of enrollment.
Certificate of Completion
After completion of all course units and earning a 100% class progress, learners will be awarded an official National University Professional and Continuing Education Certificate of Completion.
Refund Policy
We at National University want all of our students to have a positive and rewarding learning experience. In the event that a student is not completely satisfied with a course, we offer a refund policy to ensure satisfaction.
To be eligible for a refund, the student must submit a written request, including a valid reason, within 9 calendar days of registering for the course. Additionally, the student must not have attempted more than 25% of the course.
To request a refund, email PACE@nu.edu and include your full name, student ID, and course name. Your reason for requesting a refund will be carefully reviewed, and we reserve the right to refuse a refund if we determine the request to be invalid.
If you meet the eligibility criteria and are approved for a refund, we will issue a refund to your original method of payment within 60 days of the refund approval.
How to Access My Course
Allow up to 24 hours after enrollment for the course to appear in Brightspace. (An error will appear if accessed before 24 hours)
Follow the steps below:
- Log in to your student portal at westraining.nu.edu
- Click “Login”, then “Student Login”
- Log in using User Name (email address) and Password
- In your PACE student portal, click on “Brightspace LMS” on the left-hand navigation panel.
- Under My Courses, click the course title to get started.
Applies Towards the Following Certificates
- Python for Data Science : Python for Data Analytics