Prerequisite
NoneTrainers
Course architecture
1. Introduction to Artificial Intelligence
- Definition of AI: Basic concepts and terminology
- Differentiating between human and artificial intelligence
- Common applications of AI in everyday life
2. History of AI
- Timeline of key advances: From the creation of ELIZA to ChatGPT
- Periods of progress and winters of AI
- Major contributors and their impact (Turing, McCarthy, Minsky, etc.)
3. Characteristics of AI
- Learning and continuous improvement
- Perception and decision-making capabilities
- Adaptability and automation
4. Types of AI and Applications
- Conversational and generative AI: ChatGPT and Copilot
- Differences and specificities of chatbots and search engines
- The importance of AI in various sectors: Healthcare, finance, education, etc.
5. Practical Uses of ChatGPT
- How LLM models work and are trained
- Practical demonstration of ChatGPT: Various use cases
- Comparison between ChatGPT and Copilot M365
6. Risks and Challenges of AI
- Limitations and biases of AI models
- Ethical issues: Data privacy and security
- Economic consequences and impact on employment
7. Tools and Extensions for Optimization
- Practical tools to maximize the use of generative AI
- Tips on prompt engineering: Structuring and tricks
8. Best Practices and Conclusion
- Strategies for responsibly integrating AI into your business
- Best practices for avoiding common mistakes
- Future prospects and ongoing development of AI
Pedagogical details
Type of training
Private or personalized training
If you have more than 8 people to sign up for a particular course, it can be delivered as a private session right at your offices. Contact us for more details.
Request a quotePrivate or personalized training
If you have more than 8 people to sign up for a particular course, it can be delivered as a private session right at your offices. Contact us for more details.
Request a quote