Academy
AI Essentials: Understand Generative AI in 20 Minutes
A plain-language introduction to how generative AI really works, where it shines, where it fails, and how to use it responsibly on OUPI. No technical background needed — just the shared vocabulary every team member should have before using any AI feature.
Programa del curso
1
What a Model Actually Does
Understand that a large language model is a text predictor, not a knowledge database, so its strengths and failures make sense.
2
Tokens and the Context Window
Learn what tokens are and how the context window acts as the model's working memory for each request, affecting cost, speed and limits.
3
Hallucinations: Why AI Invents Things
Recognise that confident-sounding false statements are an inherent property of text prediction, not a fixable bug.
4
Grounding: Documents, Search and Tools
Discover how grounding techniques — knowledge bases, web search and tools — reduce hallucinations by giving the model verified material to work from.
5
Model vs Product, Temperature and Multimodal
Distinguish the model (engine) from the product built around it, and understand key settings like temperature and multimodal capabilities.
6
From Chat to Agents
Understand the difference between a one-shot chat answer and an agent that plans, uses tools and iterates toward a goal.
7
Your Data, Memory and Privacy
Know that models do not learn from your conversations, that data is sent only for the current request, and that sovereign model options exist.
8
The Golden Rule: AI Proposes, You Validate
Apply a practical framework for deciding what to delegate to AI and what to verify, based on the stakes of the output.
Seguir este curso en OUPI
Progreso, cuestionario y certificado en tu cuenta — 8 preguntas para validar lo aprendido y obtener un certificado, en tu espacio OUPI.