Course Outline
1. Introduction to AI
-
Defining Artificial Intelligence
-
Examples of AI in everyday life
-
The importance of AI
2. Understanding AI Mechanics (Simplified)
-
Core concept: data → model → result
-
Types of learning methods:
-
Supervised learning
-
Unsupervised learning
-
Feedback-guided learning
-
3. AI Applications in Personal and Professional Contexts
-
Text generation
-
Image and document analysis
-
Voice and video recognition
4. Interacting with AI Systems
-
Understanding prompts
-
Basic principles for crafting effective prompts
-
Practical case studies
5. Ethics and Responsibility in AI
-
Potential risks and challenges
-
Strategies for data protection
6. Selecting and Utilizing AI Tools
-
Overview of accessible AI tools
-
Evaluating safety and compliance standards
7. The Future of AI and Preparation Strategies
-
Current and emerging trends
-
Essential skills for future readiness
8. AI's Impact on Business
-
Opportunities AI brings to the workplace
-
Challenges AI introduces to professional environments
-
Industry-specific practical examples
This curriculum is applicable to any type of AI system, including popular tools such as ChatGPT, Copilot, and others.
Requirements
Foundational 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