Artificial Intelligence (AI): AI Resources

Offered by the University of Helsinki and MinnaLearn, this course provides a non-technical introduction to AI, covering its basics, applications, and societal implications. It's available in multiple languages and is ideal for those new to the field.

Google offers a range of courses from introductory to advanced levels, covering topics like TensorFlow, Vertex AI, and MLOps, with hands-on labs and real-world applications.

IBM offers a series of free courses covering AI basics, including natural language processing and ethical considerations. Learners can earn digital badges upon completion.

This course focuses on applying deep learning techniques using the fastai library and PyTorch. It's project-based and suitable for those with basic Python knowledge.

This article explores the phenomenon of "hallucinations" in large language models like ChatGPT, where the AI generates plausible-sounding but factually incorrect information. It highlights the potential dangers of relying on AI for scientific writing, as fabricated citations or data can mislead readers and compromise academic integrity. The article stresses the need for verification and critical review when using AI tools in scholarly contexts.

This systematic review investigates how users perceive and interact with explainable AI (XAI) systems. It identifies key dimensions influencing user trust, such as transparency, comprehensibility, and context relevance. The article emphasizes the importance of user-centered design in making AI explanations meaningful and actionable, especially in high-stakes domains like healthcare and finance.

Published in TechTrends, this article introduces practical strategies for educators to effectively use prompt engineering, including components like persona, aim, recipients, and tone

The article examines how AI-generated text detectors disproportionately flag writing by non-native English speakers as likely to be AI-generated. This raises issues of fairness, discrimination, and the limitations of current AI detection tools. The article calls for more equitable and inclusive detection mechanisms that account for diverse linguistic backgrounds.

This piece evaluates the growing use of AI chatbots, particularly ChatGPT, by students for academic work. While the chatbot can generate essays and answer questions, the article notes that the quality often lacks depth, accuracy, and critical thinking. It discusses ethical concerns, the role of educators in adapting to AI tools, and why human oversight remains essential in learning environments.

This article introduces prompt engineering as a critical skill in effectively using generative AI tools like ChatGPT. It outlines techniques for crafting precise and creative prompts to elicit better responses, such as framing, role-setting, and iterative refinement. The article also discusses how prompt engineering can improve productivity, creativity, and the responsible use of AI.