Artificial Intelligence & Leadership Organization
Artificial Intelligence level 1
Chapter 1. AI - Definition and key concepts
Chapter 2. Importance of data - quality and selection
Chapter 3. AI development - Driving forces
Chapter 4. Overview - Prediction, robotics, vision, generative AI and their various technologies and methods
Chapter 5. AI techniques - Search, classification and object recognition
Chapter 6. Methods and algorithms - Decision trees, regression and supervised/unsupervised learning
Practical
Chapter 7. AI problem-solving - The process
Chapter 8. Simpler forms of problem-solving - Classification, object recognition, prediction, NLP, BML and game agents
Chapter 9. Principles and applications of common techniques - Machine learning and robotics
Chapter 10. Easier AI training - Methods
Approach
Chapter 11. Problem solving comparison - Simpler AI and human solutions
Chapter 12. Superior in different situations - AI or humans
Chapter 13. AI law - Norms, laws and regulations
Chapter 14. Ethics - Dilemmas and transparency
Chapter 15. Opportunities and risks - Democratic, social, economic, environmental, security-related and consequences for society
Artificial Intelligence level 2
Chapter 1. Specific fields - Social media, healthcare and transportation
Chapter 2. Techniques, methods and algorithms
Chapter 3. Applications
Practical
Chapter 4. Problemsolving process - Quality assurance, deployment and maintenance of solution
Chapter 5. Largescale problemsolving - Classification, object recognition, prediction, NLP game agents
Chapter 6. Problemsolving algorithms - Machine learning, game agents, prediction and robotics
Chapter 7. Strengths and weaknesses of methods - Search, classification and machine learning
Chapter 8. Building blocks - Artificial neural networks
Chapter 9. Training machine learning systems - Labeled and unlabeled data, training data and test data
Chapter 10. Deep neural networks - Use and configuration
Approach
Chapter 11. Evaluation of problemsolving - AI compared to humans
Chapter 12. Laws and regulations - Consequences for AI
Chapter 13. Opportunities and consequences - Democratic, ethical, social, economic, environmental and security-related
Chapter 14. Risk assessment - Various situations
Chapter 15. Weaknesses in machine learning - Transparency, logical explanations of output, data selection and data quality
Leadership & Organization level 1
Chapter 1. Leadership theories - Concepts, theories and models
Chapter 2. Group processes - within a group, consequences of behavior and phases
Chapter 3. Group development for desired results - Assembled, organized and led
Chapter 4. Conflicts - Managed and prevented
Chapter 5. Factors - Communication, collaboration and motivation
Chapter 6. Various situations - Styles, roles, goals, effectiveness, personal leadership development and how to utilize resources
Chapter 7. Changes in the external environment - Need for organizational changes
Chapter 8. Organizational culture - Assumptions, values, norms and the influence on leadership, employees and results
Chapter 9. Ethical awareness, democratic values, gender equality, diversity and discrimination
Chapter 10. Analysis of leadership - Reflection on news and trends
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