The Machine Learning Engineer Courses

LLMOps - MCP Client: Connecting Python and JavaScript MCP Servers

Discover cómo construir un Cliente MCP que transforma Claude AI en un asistente financiero profesional capaz de analizar acciones, buscar en Google y generar reportes automáticamente.

• YouTube
• 56 minutes
• Self-Paced
• Free Video

Model Context Protocol (MCP): Introduction and Example in Python - Client and Server Implementation

Explore the Model Context Protocol (MCP) through a practical Python implementation, learning how this open standard enables AI models to connect with external tools and data sources through a standardized interface.

• YouTube
• 58 minutes
• Self-Paced
• Free Video

LLMOps: MCP Servers - Practical Example of Research and Mailing Tools

Descubre el protocolo MCP para LLMOps, aprendiendo a crear aplicaciones cliente-servidor con SSE y a implementar herramientas prácticas de investigación y correo que se integran con Google, Brave y Gmail.

• YouTube
• 55 minutes
• Self-Paced
• Free Video

MLOps MLflow: Fine-tune LLaMA 3.2 3B with PEFT, QLoRA, and DORA for Customer Service

Master fine-tuning techniques for LLama 3.2 3B model using QLora and DORA, specifically focused on creating customer service chatbots with specialized datasets and MLflow integration.

• YouTube
• 33 minutes
• Self-Paced
• Free Video

MLOps MLflow: Fine-tuning Llama 3.2 3B with PEFT, QLora and DORA for Customer Service - Spanish

Aprende a realizar fine-tuning del modelo LLama 3.2 3B usando QLora y DORA para crear bots especializados en servicio al cliente, con implementación práctica en MLflow.

• YouTube
• 35 minutes
• Self-Paced
• Free Video

Managing Multiple Python Versions and Environments with Pyenv

Master Pyenv for managing multiple Python versions and environments, streamlining your development workflow with efficient version control and environment management techniques.

• YouTube
• 24 minutes
• Self-Paced
• Free Video

MLOps: Managing Python Versions and Environments with Pyenv

Aprende a gestionar múltiples versiones de Python y crear entornos aislados con Pyenv, una herramienta esencial para el desarrollo eficiente de proyectos de machine learning.

• YouTube
• 22 minutes
• Self-Paced
• Free Video

MLOps: Apache Tika - The Content Analysis Toolkit for Data Science and Machine Learning

Explore Apache Tika's powerful capabilities for extracting metadata and text from diverse file formats, streamlining content analysis and search engine indexing processes.

• YouTube
• 31 minutes
• Self-Paced
• Free Video

Apache TIKA - Toolkit de Análisis de Contenidos para MLOps

Descubre Apache Tika, una potente herramienta para extraer metadatos y texto de más de mil formatos de archivos diferentes, simplificando el análisis de contenido y la indexación de datos.

• YouTube
• 40 minutes
• Self-Paced
• Free Video

Building Local Agents with LangGraph, Llama 3.2, and Chroma Vector Store

Master building local AI agents using LangGraph, integrating Chroma vector store and Llama 3.2 8B for efficient data retrieval and processing capabilities.

• YouTube
• 45 minutes
• Self-Paced
• Free Video

Building a Local RAG Agent with LangGraph, LLama 3.2 8B, Chroma, and Ollama

Aprende a construir un agente local RAG utilizando LangGraph, integrando Chroma Vector Store con embeddings de Nomic.ai y el modelo Llama 3.2 8B para procesamiento de lenguaje natural.

• YouTube
• 54 minutes
• Self-Paced
• Free Video

Building RAG Applications with PDFs Using LlamaIndex - Comparing Gemini Pro and Nvidia NIM Llama 3.2

Master RAG implementation using LlamaIndex to create PDF-based conversational agents with Gemini Pro and Nvidia NIM Llama 3.2, leveraging PymuPDF for text and image extraction.

• YouTube
• 28 minutes
• Self-Paced
• Free Video

RAG - Extracting Information from PDFs Using LlamaIndex, Gemini, and Nvidia NIM with Llama 3.2

Aprende a extraer información de PDFs utilizando LlamaIndex, implementando modelos como Gemini y Nvidia NIM para embeddings junto con LLama 3.2 para procesamiento de lenguaje natural.

• YouTube
• 41 minutes
• Self-Paced
• Free Video

vLLM Inference and LLM Server Engine for Machine Learning

Discover how to leverage vLLM for efficient large language model inference and serving, including practical implementation techniques and deployment strategies.

• YouTube
• 46 minutes
• Self-Paced
• Free Video

vLLM - Servidor Especializado en Inferencia de LLMs

Descubre cómo implementar y optimizar servidores de inferencia LLM con vLLM, una tecnología especializada para el procesamiento eficiente de modelos de lenguaje a gran escala.

• YouTube
• 43 minutes
• Self-Paced
• Free Video