By completing this beginner-friendly course, learners will be able to set up Python environments, manipulate data using NumPy, and create insightful visualizations with Matplotlib and Seaborn. Designed for those starting their journey in Artificial Intelligence, the course ensures students build a strong computational foundation before progressing to advanced AI concepts.
AI Foundations with Python: Build & Visualize
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AI Foundations with Python: Build & Visualize
This course is part of Artificial Intelligence with Python: Foundations to Projects Specialization
Instructor: EDUCBA
Included with 
Gain insight into a topic and learn the fundamentals.
5 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Set up Python environments with Anaconda and Jupyter.
Manipulate and analyze data efficiently using NumPy.
Create clear, insightful visualizations with Matplotlib & Seaborn.
Skills you'll gain
Details to know
Shareable certificate
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Recently updated!
September 2025
Assessments
7 assignments
Taught in English
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This course is part of the Artificial Intelligence with Python: Foundations to Projects Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 2 modules in this course
This module introduces learners to the fundamental tools required for Artificial Intelligence development in Python. Students will begin by setting up their environment with Anaconda Navigator and Jupyter Notebook, ensuring a smooth workflow for AI projects. The module then dives into NumPy, a core library for scientific computing, covering array creation, indexing, selection, and filtering techniques. By the end of this module, learners will have the ability to manipulate data efficiently and build a strong computational foundation essential for AI applications.
What's included
7 videos3 assignments1 plugin
This module focuses on transforming raw data into meaningful visuals using Python’s powerful visualization libraries. Students will begin by exploring Matplotlib for creating fundamental plots such as line, bar, and histogram charts. They will then advance to Seaborn, a high-level visualization library, to generate aesthetically pleasing statistical graphs, including heatmaps and box plots. The module concludes with hands-on work in scatter plots and practical Seaborn applications, equipping learners with the skills to interpret and communicate AI data insights effectively.
What's included
10 videos4 assignments
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