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    Prof. Ryan Ahmed
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    Reseña del curso LLM Engineering, RAG, & AI Agents Masterclass [2026] de Prof. Ryan Ahmed

    Opiniones de la comunidad

    Master Large Language Models, Retrieval Augmented Generation, LangGraph, MCP, CrewAI, AutoGen, N8N, & OpenAI Agents SDK

    Formato de aprendizaje Online Course
    Subcategoría AI Agents

    Precio del curso $19.99 (list $9.99)

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    ¿El curso de Prof. Ryan Ahmed es legítimo?

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    Sobre Prof. Ryan Ahmed

    Master Large Language Models, Retrieval Augmented Generation, LangGraph, MCP, CrewAI, AutoGen, N8N, & OpenAI Agents SDK

    ¿Quién es Prof. Ryan Ahmed?

    No hay biografía disponible.

    Sector

    AI

    Total de estudiantes

    12,696 students

    Sitio web oficial

    —

    Experiencia

    Idioma del curso

    English

    Redes sociales

    Ubicado en

    ¿Qué se aprende en el curso de Prof. Ryan Ahmed?

    Understand the foundations of Large Language Models (LLMs) and Agentic AI, including how LLMs are trained, fine-tuned, and deployed.
    Create and deploy intelligent autonomous AI agents using cutting-edge frameworks like AutoGen, OpenAI Agents SDK, LangGraph, n8n, and MCP.
    Explore and benchmark open-source LLMs such as LLama, DeepSeek, Qwen, Phi, and Gemma using Hugging Face and LM Studio.
    Develop real-world applications using API access to OpenAI, Gemini, and Claude for text generation and vision tasks.
    Apply a proven 5-step framework to select the right AI model for your business: maximizing cost-efficiency, minimizing latency, & accelerating time to market.
    Evaluate LLMs using leaderboards like Vellum and Chat Arena, and conduct blind tests to objectively assess AI model performance.
    Design Retrieval-Augmented Generation (RAG) pipelines using LangChain, OpenAI embeddings, & ChromaDB for efficient document retrieval & question answering.
    Build an interactive, transparent AI-powered Q&A system with a Gradio interface that displays answers along with source citations for enhanced user trust.
    Master data validation & structured output generation using the Pydantic library, including BaseModel, type hints, & parsed output creation from OpenAI models.
    Build an AI-powered resume editor that analyzes gaps between a resume & job description & automatically tailors resumes/cover letters for targeted applications.
    Learn how to fine-tune pre-trained open-source LLMs using parameter-efficient methods like LoRA and tools such as Hugging Face’s TRL and SFTTrainer.
    Master dataset preparation and model evaluation techniques, including calculating accuracy, precision, recall, and F1-score using scikit-learn.
    Apply key components in Hugging Face Transformers library such as pipeline( ), AutoTokenizer( ), and AutoModelForCausalLM( ).
    Gain practical experience working with open-source datasets/models on Hugging Face, & apply quantization techniques like bitsandbytes to optimize Performance.
    Master advanced prompt engineering techniques such as zero-shot, few-shot, and chain-of-thought prompting.
    Deploy multi-model AI agents using AutoGen, integrating LLMs from OpenAI, Gemini, & Claude, enabling agent collaboration & human-in-the-loop oversight.
    Develop and deploy agentic AI workflows using LangGraph, mastering concepts like states, edges, conditional logic, and multi-stage nodes.
    Design & build AI-powered booking agents using LangGraph, enabling automated search & recommendation of flights & hotels through integration with external APIs.
    Build a data science agent team using CrewAI, creating specialized agents for workflow planning, data analysis, model building, and predictive analytics.
    Design and automate end-to-end Agentic AI workflows using n8n, integrating services like Gmail, Google Sheets, Google Calendar, and OpenAI.
    Build an advanced AI tutor system using Model-Context-Protocol (MCP) and OpenAI Agents SDK, enabling dynamic tool interoperability.
    Apply classical ML models (linear regression, random forest, XGBoost) within agent workflows, including dataset loading and inspection.

    ¿Qué incluye este curso?

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