Bruges

NH Hotel Bruges, Boeveriestraat 2, Bruges, Belgium, 8000

Bruges became a central port, commercial and financial hub in medieval Europe, linking the countries of the North Sea and the Baltic to the Mediterranean. Wealthy merchants from Bruges traded with those from all over Europe. The first stock exchange in history was born in Bruges in the 13th century. In the 15th century it was the leading financial center in Europe. This economic boom also leads to a cultural and artistic flowering that has left an abundant heritage. It was the most important center for the Flemish primitive painters, who revolutionized Western painting. It has been a member of the Organization of World Heritage Cities since the year 2000. The city even has the distinction of appearing three times on the UNESCO World Heritage List. For its historic center, for its beguinage which is part of the Flemish Beguinages and for its belfry included among the Belfries of Belgium and France. In addition, it is also listed as Intangible Cultural Heritage of Humanity by UNESCO for its Procession of the Holy Blood.

  • The nearest airport to the training center

  • OSTEND-BRUGES INTERNATIONAL AIRPORT

  • Closest train station to the training center

  • Brugge Station

  • The closest car park to the training center

  • Interparking 't Zand

  • Cafés restaurants bars nearby

    1. Leffe Restaurant
    2. Bocca Restaurant
    3. Bar Parazzar

    Subcategories (2)

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    Large Language Models Meta AI

    21 Hours

    Generative AI and Large Language Models (LLMs)

    14 Hours

    Ethical Deployment of LLMs

    7 Hours

    Cross-Lingual LLMs

    14 Hours

    LLMs for Financial Market Prediction

    14 Hours

    LLMs for Environmental Modeling

    14 Hours

    LLMs for Virtual Reality (VR) and Augmented Reality (AR)

    14 Hours

    LLMs in Multimodal Applications

    14 Hours

    LLMs for Cybersecurity

    14 Hours

    LLMs for Predictive Analytics

    14 Hours

    Large Language Models (LLMs) and Reinforcement Learning (RL)

    21 Hours

    LLMs for Content Generation

    14 Hours

    LLMs for Personalized Education

    14 Hours

    Fine-Tuning Open-Source LLMs (LLaMA, Mistral, Qwen, etc.)

    14 Hours

    LLMs for Speech Recognition and Synthesis

    14 Hours

    LLMs for Automated Customer Support

    14 Hours

    Parameter-Efficient Fine-Tuning (PEFT) Techniques for LLMs

    14 Hours

    Fine-Tuning Large Language Models Using QLoRA

    14 Hours

    LLMs for Sentiment Analysis

    21 Hours

    LLMs for Code Generation and Documentation

    14 Hours

    LLMs for Business Intelligence

    14 Hours

    LlamaIndex: Developing LLM Powered Applications

    42 Hours

    Ethical Considerations in AI Development with LangChain

    21 Hours

    LlamaIndex: Enhancing Contextual AI

    14 Hours

    Enhancing User Experience with LangChain in Web Apps

    14 Hours

    Google Gemini AI for Data Analysis

    21 Hours

    Prompt Engineering and Few-Shot Fine-Tuning

    14 Hours

    Automating Workflows with LangChain and APIs

    14 Hours

    Google Gemini AI for Content Creation

    14 Hours

    Google Gemini AI for Transformative Customer Service

    14 Hours

    LangChain for Data Analysis and Visualization

    14 Hours

    Introduction to Google Gemini AI

    14 Hours

    Integrating LangChain with Cloud Services

    14 Hours

    Building Conversational Agents with LangChain

    14 Hours

    Fine-Tuning and Customizing AI Models on Ollama

    14 Hours

    Generative AI with Large Language Models (LLMs)

    21 Hours

    AI Automation with n8n and LangChain

    14 Hours

    Building Private AI Workflows with Ollama

    14 Hours

    Deploying and Optimizing LLMs with Ollama

    14 Hours

    Fine-Tuning Models and Large Language Models (LLMs)

    14 Hours

    LangChain Fundamentals

    14 Hours

    Advanced LLMs for NLP Tasks

    21 Hours

    LangChain: Building AI-Powered Applications

    14 Hours

    Introduction to Large Language Models (LLMs)

    14 Hours

    Getting Started with Ollama: Running Local AI Models

    7 Hours

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