Foundations of Artificial Intelligence: Symbolic and Rule-Based Reasoning

Free Symbolic AI and Rule-Based Reasoning Course for Beginners

Before artificial intelligence learned from massive datasets, it tried to reason through symbols, rules and logic.

Foundations of Artificial Intelligence: Symbolic and Rule-Based Reasoning is a free beginner-friendly AI course from NORAI Academy. It introduces the logic-driven roots of artificial intelligence, including Symbolic AI, rule-based reasoning, expert systems, knowledge bases, inference engines, fuzzy logic and evolutionary computation.

This course is designed as an accessible follow-up to Foundations of Artificial Intelligence: From Myths to Machine Learning. It helps you understand how early AI researchers tried to recreate human reasoning using explicit rules, structured knowledge and formal logic – and why those ideas still matter today.

You do not need coding experience or a technical background to begin.

You’ll learn how Symbolic AI, sometimes called Good Old-Fashioned AI, represented knowledge through symbols and “if-then” rules. You’ll explore how expert systems were built to imitate specialist decision-making in fields such as medicine, law, finance, engineering and troubleshooting. You’ll also learn why these systems were powerful, why they were limited, and how their ideas continue to influence explainable AI, hybrid AI systems and modern approaches to artificial intelligence.

The course also introduces important ideas beyond strict rule-based systems, including fuzzy logic for handling grey areas and uncertainty, and evolutionary computation for solving complex problems through nature-inspired methods such as genetic algorithms and swarm intelligence.

Who is this for?

This course is for anyone who wants to understand the foundations of AI reasoning before moving deeper into machine learning, neural networks and generative AI.

It is suitable for:

– beginners who want to understand how early AI systems worked
– students learning artificial intelligence fundamentals
– professionals who want to understand rule-based systems and expert systems
– entrepreneurs and decision-makers interested in explainable AI
– creators, consultants and lifelong learners who want clearer AI knowledge
– anyone curious about how machines can use rules, logic and structured knowledge to solve problems

By the end of the course, you will understand the basic principles of symbolic AI, how expert systems use knowledge bases and inference engines, why rule-based AI struggled with ambiguity and scalability, and how fuzzy logic and evolutionary computation expanded the field beyond rigid yes-or-no reasoning.

Complete the course and quizzes to earn your free NORAI Academy certificate.

Based on Victor A. Lausas’ acclaimed book, “Artificial Intelligence Made Unlocked” (ISBN 978-952-88-0520-5), this course distils the essentials for anyone ready to understand and apply AI in the real world. If you prefer to read the book instead, you can also get the book for free for a limited time:

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The book is also on shelves at Lulu for 19.99€.

FAQ

What is Symbolic AI? 
Symbolic AI is an approach to artificial intelligence that uses symbols, rules and logic to represent knowledge and perform reasoning. Instead of learning from data like modern machine learning systems, symbolic AI works by following explicit rules such as “if this is true, then do that.”

What is rule-based reasoning in AI? 
Rule-based reasoning is a method where an AI system makes decisions by applying predefined rules to information. These rules are often written as “if-then” statements and are used to draw conclusions, classify situations or recommend actions.

Is this Symbolic AI course free? 
Yes. Foundations of Artificial Intelligence: Symbolic and Rule-Based Reasoning is currently available as a free course through NORAI Academy.

Is this course suitable for beginners? 
Yes. This course is beginner-friendly and designed for learners who want to understand how early AI systems worked before moving deeper into machine learning, neural networks and generative AI.

Do I need coding skills to take this course? 
No. This is not a programming course. It explains symbolic AI, rule-based systems, expert systems, fuzzy logic and evolutionary computation in clear, accessible language.

What is an expert system? 
An expert system is a type of AI designed to imitate the decision-making of a human specialist. Expert systems usually include a knowledge base, an inference engine and a user interface, allowing them to apply rules and provide recommendations in specific domains such as medicine, law, finance or troubleshooting.

Why is Symbolic AI important? 
Symbolic AI is important because it helped establish many of the early foundations of artificial intelligence. It introduced ideas such as structured knowledge, logical reasoning, expert systems, explainability and rule-based decision-making — concepts that still influence AI today.

What are the limitations of rule-based AI? 
Rule-based AI can struggle with ambiguity, uncertainty, exceptions and real-world complexity. Because the rules usually need to be created manually, these systems can become difficult to scale, update and maintain.

Does this course cover fuzzy logic? 
Yes. The course introduces fuzzy logic as a way to handle grey areas and uncertainty beyond simple true-or-false reasoning.

Does this course cover evolutionary computation? 
Yes. The course introduces evolutionary computation and nature-inspired problem-solving, including ideas such as genetic algorithms and swarm intelligence.

Who is this course for? 
This course is for beginners, students, professionals, entrepreneurs, consultants and lifelong learners who want to understand the logic-driven roots of artificial intelligence and how machines can use rules, symbols and structured knowledge to solve problems.

Can I earn a certificate? 
Yes. Complete the course and quizzes to earn your free NORAI Academy certificate.

Is this course based on a book? 
Yes. The course is based on Victor A. Lausas’ book Artificial Intelligence Made Unlocked: From Logic to Learning, which covers symbolic AI, expert systems, fuzzy logic, evolutionary computation, machine learning, deep learning, ethics, privacy, regulation and the future of AI.