AI Foundations with Python: Build & Visualize

This course is part of Artificial Intelligence with Python: Foundations to Projects Specialization

Instructor: EDUCBA

Access provided by Chulalongkorn University

2 modules

Gain insight into a topic and learn the fundamentals.

18 reviews

6 hours to complete

Flexible schedule

Learn at your own pace

2 modules

Gain insight into a topic and learn the fundamentals.

18 reviews

6 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

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

7 assignments

Taught in English

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Build your subject-matter expertise

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.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 2 modules in this course

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.

Through step-by-step guidance, learners will first configure Anaconda Navigator and Jupyter Notebook for a seamless workflow, then apply NumPy for array functions, indexing, and filtering techniques essential in AI data handling. Moving forward, they will implement Matplotlib for basic plots and transition to Seaborn for high-level, visually appealing statistical visualizations, including scatter plots, heatmaps, and box plots. What makes this course unique is its practical, project-oriented approach that blends setup, numerical computation, and data visualization into one cohesive learning path. By the end, learners will have both the technical skills and the confidence to explore real-world AI projects, effectively preparing them for more advanced machine learning and deep learning studies.

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 assignments

7 videos Total 57 minutes

Introduction to Course 7 minutes
Download Anaconda Navigator 9 minutes
Set up and Installation 8 minutes
Numpy in Jupyter Notebook 9 minutes
Array Function 7 minutes
Numpy indexing and Selection 10 minutes
Filter Function 6 minutes

3 assignments Total 60 minutes

Graded Quiz - Foundations of Python for AI 30 minutes
Getting Started with AI Tools 15 minutes
Untitled 15 minutes

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.