Elements of AI
Overview
The goal of this course is to demystify AI
The elements of AI is a free online course for everyone interested in learning what AI is, what is possible (and not possible) with AI, and how it affects our lives – with no complicated math or programming required. By completing the course you can earn a LinkedIn certificate. People in Finland can also earn 2 ECTS credits through the Open University. The course is available from May 14, 2018. Elements of AI is an introductory course that was launched in 2018 by Finnish innovation company education company Reaktor and the University of Helsinki, Finland under the framework of the 2019 Finnish Presidency of the European Council.
After taking the course, you will be able to:
- Understand some of the major implications of AI
- Think critically about AI news and claims
- Define and discuss what AI is
- Explain the methods that make AI possible
Elements of AI in brief
- Elements of AI is a free online course that offers easy-to-understand information and practical exercises on the basics of artificial intelligence.
- The course was created by the University of Helsinki and MinnaLearn in 2018.
- The course includes self-study resources, interactive content, and tasks that require approximately 30 hours of work. Students learn about artificial intelligence concepts, usage methods, and limitations. The course is suitable for anyone interested in learning the basics of AI regardless of their coding skills.
- Elements of AI has become one of the most popular online courses in the world with more than one million people from 170 countries having signed up for it. The course has been localized in 30 different countries and is available in 26 languages.
- The course has attracted a diverse group of users. Women make up 40% of the course participants, and over 25% of the users are over 45 years old.
- In 2019, Elements of AI was selected as the best computer science online course in the world, when it took first place among Class Central’s 1167 online courses.
- Anyone can take the course for free at elementsofai.com
Syllabus
Part 1
What is AI?
- How should we define AI?
- Related fields
- Philosophy of AI
Part 2
Solving problems with AI
- Search and problem solving
- Solving problems with AI
- Search and games
Part 3
Real world AI
- Odds and probability
- The Bayes rule
- Naive Bayes classification
Part 4
Machine learning
- The types of machine learning
- The nearest neighbor classifier
- Regression
Part 5
Neural networks
- Neural network basics
- How neural networks are built
- Advanced neural network techniques
Part 6
Implications
- About predicting the future
- The societal implications of AI
- Summary
Please join the Elements of AI community to discuss and ask questions.