Elements of AI: a thoughtful introduction, but a theoretical one
Open Elements of AI: Introduction to AI · Free online course · Six chapters
Elements of AI: Introduction to AI is a free course from the University of Helsinki and MinnaLearn. It has six chapters:
- What is AI?: Definitions, related fields and philosophical questions, including the Chinese Room thought experiment.
- AI problem solving: Search, problem-solving methods and games.
- Real-world AI: Probability, Bayes' rule and a spam-filter example using Naive Bayes.
- Machine learning: Types of learning, nearest-neighbour classification and regression.
- Neural networks: The basics, how networks are built and more advanced techniques.
- Implications: Predictions about the future and AI's effects on society.
I found it informative, but more like an introductory university course than practical training for someone who wants to use AI in an office job. It explains the ideas behind AI through concepts, exercises and puzzles. Chapter 3, for example, works through probability and spam filtering.
That gives you useful background, but there is less focus on practising everyday tasks with AI tools. If you want examples for emails, documents, research or other office work, you may find it takes a while to get to them.
There is a workplace angle: MinnaLearn also offers an LMS version for organisations. That means jobseekers may encounter Elements of AI if a future employer has bought it as staff training. It is a solid choice for understanding AI fundamentals, but I would not make it my first choice for learning how to use AI in day-to-day office work.
OpenAI Academy: AI Foundations
Open AI Foundations · Free with a ChatGPT account · About 60–75 minutes
AI Foundations is the introductory course in OpenAI Academy's Apply AI at Work pathway. It covers AI and large language models, how ChatGPT works, writing clearer prompts, providing useful context, reviewing responses and using AI responsibly. The activities include workplace scenarios and knowledge checks—for example, deciding whether to ask ChatGPT to revise an answer, check its logic or verify information.
This is a much more practical introduction for someone who wants to start using AI at work. It gives you enough background to understand the very basics of what you are using, then moves into examples and habits you can try. You can follow along with a free ChatGPT account, which is the whole hook of the training course.
The presentation style may not suit everyone. I found the presenter and some of the polished, mission-led language irritating, and the course has a distinctly American corporate feel. It is good practice for the fist-gnawing irritation that dealing with ChatGPT can provoke over the long term—but there is no doubting that the practical material is useful. I liked the scenario-based checks once I had worked out how they operated. It is definitely not a course to do on autopilot; it involves a fair bit of thinking.
This is the first course in a wider pathway. Applied AI Foundations moves on to building repeatable workflows; Agents and Workflows covers delegating structured tasks while setting boundaries and checking the results. If those terms do not mean much to you yet, start with AI Foundations: for a beginner who wants a practical starting point, it is the better fit.
See the full Apply AI at Work pathway
