Elements of AI | AI Course

Course snapshot

AI Basics
Problem Solving with AI
Machine Learning Foundations
Neural Networks
Bayesian Methods
Societal Implications of AI

Introduction to AI is the first part of the Elements of AI program, a free online course designed to make artificial intelligence accessible to everyone. No prior math or programming knowledge is required. The course begins with a simple question: What is AI? Learners are introduced to different definitions of AI, related fields, and the philosophical foundations of the discipline. The second chapter covers problem solving, including search strategies, algorithms for solving problems, and the role of games in testing AI systems. In Chapter 3, the focus shifts to real world AI with topics like probability, Bayes rule, and naive Bayes classification, showing how AI can be used to handle uncertainty. Chapter 4 introduces machine learning, covering the types of learning, nearest neighbor classification, and regression. Chapter 5 moves into neural networks, explaining their basics, how they are built, and advanced techniques. Finally, Chapter 6 discusses the implications of AI, including predicting the future and examining the societal impacts of widespread AI adoption. By completing the course, learners gain a broad and practical understanding of what AI is, how it works at a conceptual level, and how it is likely to affect individuals and society. The program is offered by the University of Helsinki and MinnaLearn, available globally in multiple languages, and includes a free digital certificate upon completion.

Perfect forBeginners curious about AI, Students from any background, Professionals needing AI literacy

Not forLearners expecting advanced programming, Those seeking applied machine learning projects

Price0.00–0.00 USD

Pricing and availability can change. Always check the provider page.