0. Genai. Master In Data Science

LLMs, Artificial Intelligence, Gemini, Groq, Ollama

What you'll learn

Artificial Intelligence

LLMs

Gemini

Groq

Ollama

Requirements

Python

Data Science

Description

Introduction to Generative AIYou 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 LLMsYou 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 EngineeringYou will explore how language models work, how to structure effective prompts, and how to adapt their responses to different contexts.Data Processing for Generative ModelsYou will discover strategies to prepare text, images, and documents, facilitating their use in generation and query tasks.Inference, Fine-Tuning, and EmbeddingsYou 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 MultimodalityYou will study how to integrate information retrieval, contextual reasoning, and multimodal analysis into practical applications.Practical ProjectsInvoice 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.This course provides comprehensive training in generative AI, combining theory and practice to develop skills applicable to automation, advanced analysis, and the creation of intelligent solutions.

Overview

Section 1: Introduction Theory, Environments and Front

Lecture 1 LLM Theory

Lecture 2 Environment

Lecture 3 Front Streamlit 1

Lecture 4 Front Streamlit 2

Lecture 5 API Keys & Tokens

Section 2: Step by Step RAG

Lecture 6 Data Loading

Lecture 7 Splitting

Lecture 8 Embeddings 1

Lecture 9 Embeddings 2

Lecture 10 Embeddings 3

Lecture 11 VectorStore

Section 3: Ollama

Lecture 12 Basic App 1

Lecture 13 Basic App 2

Lecture 14 RAG

Section 4: Gemini

Lecture 15 Basic App

Lecture 16 Architect-Legal 1

Lecture 17 Architect-Legal 2

Lecture 18 Image

Lecture 19 5 Images 1

Lecture 20 5 Images 2

Lecture 21 Scripts

Lecture 22 Chat

Lecture 23 ATS

Lecture 24 Invoice 1

Lecture 25 Invoice 2

Lecture 26 Posts

Lecture 27 SQL

Lecture 28 Image Description

Section 5: GROQ

Lecture 29 Assistant 1

Lecture 30 Assistant 2

Lecture 31 Write with Memory

Lecture 32 Mp3

All