0. GenAI. Master in Data Science

Introduction to Generative AI:
You will understand the fundamental principles of generative models, their applications, and the types of problems they solve in data science.
Evaluation of Generative Models and LLMs You will learn how to measure the quality of model outputs using criteria such as coherence, relevance, factual accuracy, and automatic text metrics.
Fundamentals of LLMs and Prompt Engineering:
You will explore how language models work, how to structure effective prompts, and how to adapt their responses to different contexts.
Data Processing for Generative Models You will discover strategies to prepare text, images, and documents, facilitating their use in generation and query tasks.
Inference, Fine-Tuning, and Embeddings:
You will analyze how to fine-tune models, use embeddings, and apply techniques like few-shot and fine-tuning for custom solutions.
RAG, Semantic Search, and Multimodality. You will study how to integrate information retrieval, contextual reasoning, and multimodal analysis into practical applications.
Practical Projects

• Invoice to Excel Conversion:
  You will create an automated workflow that extracts key data from PDF invoices and generates structured reports in spreadsheets.
• Legal Consultant with Documents:
  You will implement an LLM-based assistant capable of answering legal questions using legal texts in PDF format.
• Image Description with Text:
  You will design a model that analyzes images and generates automatic descriptions to facilitate their interpretation and search.
• SQL Queries with RAG:
  You will build a tool that allows querying databases using natural language, leveraging RAG to improve results.