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AI Proficiency in Higher Ed Institutions
Topic outline
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1. Understanding AI: Basics and terminology
Artificial Intelligence has long been part of everyday life on campus – in teaching, research, administration and student life. But what exactly is behind it?
In this chapter, you will be given an easy-to-understand introduction to the technical basics of AI. You will learn key terms, distinguish between different types of AI systems and take a look at language models. The aim is not to become an expert in programming, but to understand the connections, recognise risks and be able to make more informed decisions. After all, if you understand the mechanisms behind AI, you can use it confidently in your own context and better assess the consequences.
📢 Browse through our pages and explore the content at your own pace. To get the most out of this learning resource – and, not least, to receive a certificate of attendance – we recommend that you register for the course.
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What is Artificial Intelligence, and how do ChatGPT and similar tools actually work? In this section, you will learn about key concepts such as the Turing test, machine learning, neural networks and bias, and gain insight into how modern AI models work, their capabilities, limitations and societal impacts.
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What types of artificial intelligence are there, and how do machines learn? In this section, you will learn how AI systems can be categorised by scope and learning paradigm, which methods are relevant in a higher education context, and what lies behind terms such as ‘strong AI’, ‘supervised learning’ and ‘reinforcement learning’.
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How do neural networks learn, and what makes modern AI systems so powerful? In this section, you will gain a thorough understanding of how deep learning works, the structure of large language models (LLMs), current training methods, and innovative architectures such as Transformers, self-prompting and Chain-of-Thought.
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What can generative AI do, and how can it be used effectively in higher education? In this section, you will learn how tools for generating text, images or videos work, what potential they offer for teaching, research, administration and student studies, and what needs to be taken into account regarding data protection, copyright and transparency.
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What can ChatGPT do, and how can it be used effectively in higher education? In this section, you will learn how this AI tool works, its potential applications and its limitations, and discover how you can use it in teaching, administration, research and student studies in a considered and data-protection-compliant manner.
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How can AI be used in higher education institutions in a way that is secure, transparent and tailored to specific needs? In this section, you will learn about HAWKI, a data protection-compliant open-source platform developed specifically for the education sector, and discover how it supports collaborative working, academic traceability and digital sovereignty.
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How can Microsoft Copilot make everyday university life easier? In this section, you’ll learn how to make targeted use of the AI-powered features in Word, Excel, PowerPoint and other applications – to support teaching, research, administration or your studies – and what you should bear in mind regarding data protection, prompt quality and evaluating results.
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How do you formulate prompts so that AI tools deliver accurate and helpful results? In this section, you will learn key strategies and design elements for successful prompting – including practical tips, frameworks and further resources for use in a higher education context.
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