Artificial intelligence, or AI, is the ability of a machine to perform cognitive functions that are associated with human minds, such as perceiving, reasoning, learning, and problem solving. Explore these learning activities for foundational knowledge of AI concepts, sometimes referred to as cognitive computing. You'll be able to explain what artificial intelligence is and how it can be applied in the professional world. You have the option to complete the Artificial Intelligence Fundamentals courses to earn an IBM-recognized digital credential!
What this course is about
AI Foundations introduces you to the world of artificial intelligence — where it began, how it works, and how it’s shaping the future.
You’ll explore AI’s history, learn how machines make predictions, understand language, analyze images, and learn using neural networks inspired by the human brain. Through a hands-on simulation, you’ll also build and test your own machine learning model, giving you real experience beyond theory.
The course concludes with guidance on AI career paths so you can understand the opportunities available in this fast-growing field.
As you complete the course, you’ll earn certificates and digital credentials that you can add to your resume, LinkedIn profile, and Credly account to highlight your AI knowledge.
You’ll learn how to:
Understand core AI concepts and terminology
Explore how AI analyzes data, language, and images
Build a simple machine learning model
Plan how to pursue a career in artificial intelligence
What you will learn
By the end of this course, you will be able to:
Understand the history and evolution of AI
Describe important milestones in AI development
Understand how advancements in computing, data, and neural networks shaped modern AI
Master foundational AI concepts
Explain what AI, machine learning, and deep learning are
Understand how Natural Language Processing (NLP) helps machines interpret text
Recognize how computer vision enables machines to analyze and generate images
Understand AI and data fundamentals
Define structured, unstructured, and semi-structured data
Understand how machine learning models use data to make predictions
Describe three ways AI analyzes data
Explore practical AI applications
Understand how AI processes and creates images
Explain generative AI and its impact in today’s world
Learn responsible AI principles
Understand AI ethics, fairness, transparency, and responsible deployment
Get hands-on experience
Build and test a machine learning model using IBM Watson Studio
Explore how real AI tooling works in practice
Explore AI career pathways
Learn about roles such as machine learning engineer, data scientist, AI researcher, NLP specialist, and more
Understand the skills and learning paths needed to enter the AI field
Showcase your learning
Earn certificates and digital credentials
Add them to your resume, LinkedIn, and Credly profile to demonstrate your AI skills
This course is part of the Technology Skills learning path.