Course Outline
1. AI Fundamentals
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Defining Artificial Intelligence
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Examples from daily life
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The importance of AI
2. Understanding AI Mechanics (Simplified)
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Core concept: data → model → result
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Learning methodologies:
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Supervised learning
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Unsupervised learning
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Feedback-based learning
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3. AI in Personal and Professional Contexts
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Text generation capabilities
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Image and document analysis
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Voice and video recognition
4. Interacting with AI
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Understanding prompts
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Basic principles for crafting prompts
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Practical case studies
5. Ethical Considerations and Responsibility in AI
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Potential risks and challenges
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Strategies for data protection
6. Selecting and Utilizing AI Tools
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Overview of accessible tools
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Verifying safety and compliance standards
7. The Future Landscape of AI and Preparation Strategies
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Emerging trends
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Essential skills for the future
8. AI's Influence on Business
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Opportunities AI creates for work
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Challenges AI introduces to the workplace
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Industry-specific case examples
This course applies to all types of AI systems, including widely used tools such as ChatGPT, Copilot, and others.
Requirements
Fundamental computer literacy
Testimonials (2)
the trainer, the amount and the quality of information
ALINA UNGURU
Course - Introduction to Artificial Intelligence for Non-technical users
Hands on examples