Module 1. Introduction to Artificial Intelligence

• What is AI?
• History and evolution of AI.
• Differences between AI and traditional programming

Module 2. Types of Artificial Intelligence

• Weak AI vs. Strong AI.
• Practical examples of AI in everyday life (virtual assistants, chatbots, etc.).

Module 3. Applications of Artificial Intelligence

• AI in sectors such as healthcare, finance, transportation, and retail.
• Use of AI in task automation and efficiency improvement.

Module 3. Machine Learning Basics

• What is machine learning?
• How AI “learns” from data.
• Common applications of machine learning (product recommendations, predictions, etc.).

Module 4. Natural Language Processing (NLP)

• How do machines understand and generate text?
• Examples: chatbots and virtual assistants (Alexa, Siri, Google Assistant).

Module 5. AI in Decision Making

• How AI helps companies make data-driven decisions.
• Case study: recommendation systems on platforms like Netflix or Amazon.

Module 6. Challenges and Opportunities of Artificial Intelligence

• Current advantages and limitations of AI.
• Impact on work and society.

Module 7. Ethics and Considerations in the Use of AI

• Main ethical challenges (privacy, bias, etc.).
• The importance of responsible use of AI.

Module 8. Future of Artificial Intelligence

• Innovations and future trends.
• Impact of AI on the labor market and industries.