Lessons

Tile Name Grade Deadline
L0: Introduction to AI I. Journey into the history of the artificial intelligence field 0 No deadline
L0: Introduction to AI II. Artificial intelligence systems in your own life 0 No deadline
L0: Introduction to AI III. Artificial intelligence systems in society 0 No deadline
L0: Introduction to AI IV. Artificial Intelligence systems across domains 0 No deadline
L0: Introduction to AI V. Concerns related to artificial intelligence systems 0 No deadline
L0: Introduction to AI VI. Capabilities of AI systems 0 No deadline
L0: Introduction to AI I. Reasons why future professionals should learn about AI 0 No deadline
L0: Introduction to AI II. Competencies for professionals in an AI world 0 No deadline
L0: Introduction to AI I. Responsible use of LLMs 0 No deadline
L1: Digitization I. Analog Digital Tinder 0 No deadline
L1: Digitization II. Analog and digital representation 0 No deadline
L1: Digitization III. Digitization of a photo 0 No deadline
L1: Digitization IV. Analog Digital Tinder 2 0 No deadline
L1: Digitization I. How far can you count with one hand? 0 No deadline
L1: Digitization II. The binary system 0 No deadline
L1: Digitization III. The binary system and the computer 0 No deadline
L1: Digitization Excursus: The coding of colors 0 No deadline
L1: Digitization I. Input, processing and output 0 No deadline
L1: Digitization II. Hardware and software 0 No deadline
L1: Digitization III. Performance data of a computer 0 No deadline
L1: Digitization I. Internet I 0 No deadline
L1: Digitization II. Internet-experiments 0 No deadline
L1: Digitization III. Internet II 0 No deadline
L1: Digitization Excursus: WWW 0 No deadline
L2: Algorithms I. What is an algorithm? 0 No deadline
L2: Algorithms II. Algorithm yes or no? 0 No deadline
L2: Algorithms I. Programming languages: the language of digitization 0 No deadline
L2: Algorithms II. Blockly and Python welcome you! 0 No deadline
L2: Algorithms III. Variables, data types, and operations 0 No deadline
L2: Algorithms IV. Conditional statements 0 No deadline
L2: Algorithms V. Loop structures 0 No deadline
L2: Algorithms VII. Lists 0 No deadline
L2: Algorithms VI. Functions 0 No deadline
L3: What is AI? What are AI systems? I. What do you think AI is? 0 No deadline
L3: What is AI? What are AI systems? II. Perspectives on AI: Discussing definitions 0 No deadline
L3: What is AI? What are AI systems? I. In your opinion, what is an AI system? 0 No deadline
L3: What is AI? What are AI systems? II. Why should you know what an AI system is? 0 No deadline
L3: What is AI? What are AI systems? III. Traditional computer systems vs. artificial intelligence systems 0 No deadline
L3: What is AI? What are AI systems? IV. Definition of an AI system 0 No deadline
L3: What is AI? What are AI systems? V. AI system! - or maybe not? 0 No deadline
L3: What is AI? What are AI systems? VI. AI systems embedded in traditional systems 0 No deadline
L3: What is AI? What are AI systems? VII. AI techniques and AI systems 0 No deadline
L3: What is AI? What are AI systems? VIII. Discussing with colleagues 0 No deadline
L3: What is AI? What are AI systems? I. Knowledge-based AI 0 No deadline
L4: Data I. Data 0 No deadline
L4: Data II. Big Data 0 No deadline
L4: Data I. Data and AI 0 No deadline
L4: Data IV. Overview 0 No deadline
L4: Data I. Personal Data 0 No deadline
L4: Data II. Potential Data Protection Violations in Connection with AI Systems 0 No deadline
L4: Data III. Possible Solutions: Data Protection Violations in Connection with AI 0 No deadline
L4: Data IV. Potential Intellectual Property Violations in Connection with AI Systems 0 No deadline
L4: Data V. Possible Solutions: Copyright Infringements in Connection with AI 0 No deadline
L4: Data VI. Back to the Initial Question: Discuss with Colleagues 0 No deadline
L4: Data I. Data "Across Domains" 0 No deadline
L5: Machine learning - Supervised learning Establishing the connection 0 No deadline
L5: Machine learning - Supervised learning I. A journey into the supervised learning approach 0 No deadline
L5: Machine learning - Supervised learning II. Introduction to supervised learning 0 No deadline
L5: Machine learning - Supervised learning III. Supervised learning: Regression 0 No deadline
L5: Machine learning - Supervised learning IV. Supervised learning: Classification 0 No deadline
L5: Machine learning - Supervised learning V. Generalization 0 No deadline
L5: Machine learning - Supervised learning VI. Generalization: A real example 0 No deadline
L5: Machine learning - Supervised learning VII. Human supervision 0 No deadline
L5: Machine learning - Supervised learning I. Helping a farmer 0 No deadline
L5: Machine learning - Supervised learning II. Bias and fairness 0 No deadline
L5: Machine learning - Supervised learning III. Bias and human supervision 0 No deadline
L5: Machine learning - Supervised learning IV. Discussion 0 No deadline
L5: Machine learning - Supervised learning I. Problem solving in different areas with supervised learning 0 No deadline
L6: Machine learning - unsupervised learning and reinforcement learning Establishing the connection 0 No deadline
L6: Machine learning - unsupervised learning and reinforcement learning I. A journey into the unsupervised learning approach 0 No deadline
L6: Machine learning - unsupervised learning and reinforcement learning II. Introduction to unsupervised learning 0 No deadline
L6: Machine learning - unsupervised learning and reinforcement learning III. Understanding unsupervised cluster detection interactively 0 No deadline
L6: Machine learning - unsupervised learning and reinforcement learning IV. Applications of unsupervised learning 0 No deadline
L6: Machine learning - unsupervised learning and reinforcement learning I. A journey into the reinforcement learning approach 0 No deadline
L6: Machine learning - unsupervised learning and reinforcement learning II. Introduction to reinforcement learning 0 No deadline
L6: Machine learning - unsupervised learning and reinforcement learning III. Exploring reinforcement learning 0 No deadline
L6: Machine learning - unsupervised learning and reinforcement learning IV. Applications of reinforcement learning 0 No deadline
L6: Machine learning - unsupervised learning and reinforcement learning I. Recommendation systems 0 No deadline
L6: Machine learning - unsupervised learning and reinforcement learning II. Possible solutions 0 No deadline
L6: Machine learning - unsupervised learning and reinforcement learning III. Discussion 0 No deadline
L6: Machine learning - unsupervised learning and reinforcement learning I. Problem solving in different areas with unsupervised and reinforcement learning 0 No deadline
L6: Machine learning - unsupervised learning and reinforcement learning Overview: Approaches to machine learning 0 No deadline
L7: Artificial Neural Networks and Deep Learning Establishing the connection 0 No deadline
L7: Artificial Neural Networks and Deep Learning I. A journey into the technology of deep learning 0 No deadline
L7: Artificial Neural Networks and Deep Learning II. Understanding how computers learn with artificial neural networks 0 No deadline
L7: Artificial Neural Networks and Deep Learning III. Godfather of AI 0 No deadline
L7: Artificial Neural Networks and Deep Learning I. Resctrictions of AI systems 0 No deadline
L7: Artificial Neural Networks and Deep Learning II. Mitigation strategies: Transparency and explainability 0 No deadline
L7: Artificial Neural Networks and Deep Learning III. Transparency of AI systems – AI Act 0 No deadline
L7: Artificial Neural Networks and Deep Learning IV. Discussion 0 No deadline
L7: Artificial Neural Networks and Deep Learning I. Black box models “across domains” 0 No deadline
L8: Large Language Models Establishing the connection 0 No deadline
L8: Large Language Models I. Real or AI-generated? 0 No deadline
L8: Large Language Models I. Language models 0 No deadline
L8: Large Language Models II. Large language models 0 No deadline
L8: Large Language Models III. Large language models: Pretraining 0 No deadline
L8: Large Language Models IV. Key technical concepts of GPTs 0 No deadline
L8: Large Language Models V. Large language models: Finetuning 0 No deadline
L8: Large Language Models I. Understanding the problem of hallucinations and their effects 0 No deadline
L8: Large Language Models II. Other limitations of LLMs 0 No deadline
L8: Large Language Models I. Prompt Engineering and Prompt Strategies 0 No deadline
L8: Large Language Models II. Creating a good prompt 0 No deadline
L8: Large Language Models III. Practicing 0 No deadline
L8: Large Language Models IV. Discussion 0 No deadline
L8: Large Language Models I. Problem solving in various areas with large language models 0 No deadline
L9: Generative AI Establishing the connection 0 No deadline
L9: Generative AI I. Real or AI generated? 0 No deadline
L9: Generative AI II. How are image generators created? 0 No deadline
L9: Generative AI III. Real or AI generated? 0 No deadline
L9: Generative AI IV. How are audio generators created? 0 No deadline
L9: Generative AI V. Unimodal Systems vs. Multimodal Systems 0 No deadline
L9: Generative AI I. Ecological Well-Being: Introduction 0 No deadline
L9: Generative AI II. Ecological Well-Being: Minimize risks 0 No deadline
L9: Generative AI III. Discussion 0 No deadline
L9: Generative AI I. Deepfakes: Introduction 0 No deadline
L9: Generative AI II. Deepfakes: Minimize risks 0 No deadline
L9: Generative AI III. Discussion 0 No deadline
L9: Generative AI I. Trying out generative AI-systems 0 No deadline
L9: Generative AI I. Problem Solving in Various Fields with Generative AI 0 No deadline
L10: AI agents I. AI agents: Introduction and some examples 0 No deadline
L10: AI agents I. How do AI agentic systems work? 0 No deadline
L10: AI agents II. AI agents and agent based AI: Levels of autonomy 0 No deadline
L10: AI agents I. Challenges and limitations of AI agents 0 No deadline
L10: AI agents II. Discussion 0 No deadline
L10: AI agents I. Trying out AI agentic systems 0 No deadline
L10: AI agents I. Problem-solving in different domains with AI agents 0 No deadline
L11: AI Systems in the Research Workflow I. Introduction 0 No deadline
L11: AI Systems in the Research Workflow I. Idea development and research design: Possible applications, risks, and countermeasures 0 No deadline
L11: AI Systems in the Research Workflow I. Literature review with AI systems 0 No deadline
L11: AI Systems in the Research Workflow II. The limitations 0 No deadline
L11: AI Systems in the Research Workflow III. Minimizing the limitations 0 No deadline
L11: AI Systems in the Research Workflow I. Improvement of writing and communication 0 No deadline
L11: AI Systems in the Research Workflow I. ChatGPT as an author 0 No deadline
L11: AI Systems in the Research Workflow II. Images generated by AI systems: Risks in research 0 No deadline
L11: AI Systems in the Research Workflow I. Overall recommendations for the use of AI systems in scientific work 0 No deadline