It’s always a special moment when something foundational is extended – not replaced, but enriched. Today, I’m excited to share that our journey into the roots of artificial intelligence continues with the launch of a brand-new course on NORAI Connect: Foundations of Artificial Intelligence: Symbolic and Rule-Based Reasoning.
This isn’t just another online course. It’s the second chapter in a larger learning arc that began with “Foundations of Artificial Intelligence: From Myths to Machine Learning”, where we dismantled the clichés, clarified core concepts and set the stage for a deeper understanding of AI. Now, we’re going deeper – into the logic-driven legacy of symbolic AI.
Let me walk you through what’s inside – and why it matters.
Why Symbolic AI Still Matters
There’s a popular misconception floating around that symbolic AI – the kind built on logic, rules and expert systems – that it is outdated or irrelevant in the age of machine learning. That couldn’t be further from the truth.
Symbolic AI, also called “Good Old-Fashioned AI” (GOFAI), laid the groundwork for everything we know about intelligent systems today. It was the first attempt to make machines “think” by encoding rules and logical relationships. And while today’s AI headlines often focus on neural networks and massive language models, symbolic systems remain essential, especially in areas where precision, transparency and auditability are non-negotiable. Think law, medicine and enterprise compliance.
This new course brings symbolic AI back into focus, not as a relic, but as a powerful tool that still plays a vital role in hybrid and explainable AI systems.
What You’ll Learn in the New Course
I designed this course for clarity, not complexity. We’ve broken it into digestible sections, each covering one key building block of symbolic reasoning. Here’s a snapshot of what learners can expect:
1. Foundations of Symbolic AI
We begin with the essentials – what symbolic AI actually is, where it came from and how it shaped the early development of AI as a field. You’ll understand key terms like logic-based inference, production rules and why these matter.
2. Core Components: Knowledge Bases & Inference Engines
Symbolic systems are made of two parts: the knowledge base (what it knows) and the inference engine (how it reasons). This section introduces both and explains how they work together, with examples.
3. Expert Systems
You’ll learn how symbolic reasoning powers expert systems – tools that can simulate human decision-making in domains like healthcare and legal reasoning. These aren’t abstract ideas. You’ll meet real systems like MYCIN, INTERNIST-I and TAXMAN, which have been used in clinical and legal environments.
4. Applications in the Real World
From diagnosing diseases to interpreting tax law, symbolic AI is still in use today. We look at its practical applications and limitations, so you know where it shines and where it struggles.
5. Symbolic vs Data-Driven AI
Perhaps most importantly, we explore how symbolic reasoning compares to machine learning. You’ll see why neither is “better” – they serve different purposes and can be combined for powerful, explainable AI solutions.
A Course Designed for Everyone - Not Just Engineers
One of the most important principles I hold is this: AI education shouldn’t be locked behind jargon. Whether you’re a policymaker, team leader, or a tech-savvy entrepreneur, this course meets you where you are. There’s no need for coding knowledge or a mathematics background. We use plain language, real examples and a learning experience that builds your confidence lesson by lesson.
And if you’re building AI products or overseeing AI integration in your organisation, the insights you’ll gain here are far from theoretical. Understanding symbolic reasoning gives you a framework for transparency, accountability and control – things that black-box models often struggle with.
And just like with all free NORAI Connect courses, a final quiz (with unlimited attempts) helps reinforce your knowledge and awards you with your certificate.
Course Format & Access
You can find the course now live on NORAI Connect Learning Hub, where all the courses are completely free to enrol.
For returning learners who completed the first “AI Foundations” course, this one picks up right where we left off. For new users, you’re required to complete the first “AI Foundations” course first.
A Few Words About the Bigger Picture
If we want to build trustworthy AI systems in Europe – ones that align with our values and regulations – then education is non-negotiable. Symbolic AI is often overlooked, but it’s one of the most transparent and auditable forms of reasoning we have. We need more professionals who understand it. More teams who know when to use it. And more systems that blend symbolic logic with the power of machine learning.
That’s what we’re building at NORAI. Not just courses, but a foundation for Europe’s AI future – one that values clarity, ethics and real-world utility over hype – and we want to provide this education for free, for everyone.
Ready to Learn?
Enrol in the course now and explore the kind of AI that doesn’t just mimic intelligence – but reasons through it.
👉 Start here: Foundations of Artificial Intelligence: Symbolic and Rule-Based Reasoning
If you haven’t already, start from the beginning of the series on NORAI Connect, the first course is “From Myths to Machine Learning“.
Final Thought
We built this course with care – but we’re always open to feedback. If there’s a concept you want explained better, a real-world example you’d like us to add, or a follow-up topic you think we should cover, tell us. NORAI is here to serve the learning community, not broadcast at it.
Let’s raise the bar for AI education in Europe – together.
North Atlantic UK
Victor A. Lausas
Chief Executive Officer
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