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Text Summarization and Content Generation with AI (NLG)

 21 Hours
This instructor-led, live training in Portugal (online or onsite) is aimed at intermediate-level professionals who wish to gain practical skills in using NLG for automating text summarization and content generation. By the end of this training, participants will be able to:
  • Understand the core principles of NLG for text summarization and content generation.
  • Implement NLG models to summarize large documents and articles.
  • Leverage pre-trained NLG models like GPT for content creation.
  • Apply advanced techniques to fine-tune NLG models for specific content generation tasks.
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AI-Driven NLG for Chatbots and Virtual Assistants

 21 Hours
This instructor-led, live training in Portugal (online or onsite) is aimed at advanced-level professionals who wish to master AI-driven NLG techniques for chatbot and virtual assistant applications. By the end of this training, participants will be able to:
  • Understand the core principles of NLG for conversational AI.
  • Leverage deep learning techniques to enhance chatbot dialogue generation.
  • Integrate state-of-the-art NLG models like GPT-3 into chatbot frameworks.
  • Apply contextual AI for improving conversational coherence and fluidity.
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Advanced Techniques in Natural Language Generation (NLG)

 14 Hours
This instructor-led, live training in Portugal (online or onsite) is aimed at intermediate-level professionals who wish to enhance their skills in generating high-quality, human-like text using advanced NLG methods. By the end of this training, participants will be able to:
  • Understand advanced techniques for generating natural language text.
  • Implement and fine-tune transformer-based models for NLG.
  • Optimize NLG outputs for fluency, coherence, and relevance.
  • Evaluate the quality of generated text using both automated and human metrics.
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Introduction to Natural Language Generation (NLG)

 14 Hours
This instructor-led, live training in Portugal (online or onsite) is aimed at beginner-level professionals who wish to learn the basics of NLG and its role in AI and content generation. By the end of this training, participants will be able to:
  • Understand the fundamental concepts of Natural Language Generation.
  • Explore the applications of NLG in various industries.
  • Learn basic techniques for generating human-like text using AI.
  • Work with Python libraries and models to generate text.
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Python for Natural Language Generation (NLG)

 21 Hours
In this instructor-led, live training in Portugal, participants will learn how to use Python to produce high-quality natural language text by building their own NLG system from scratch. Case studies will also be examined and the relevant concepts will be applied to live lab projects for generating content. By the end of this training, participants will be able to:
  • Use NLG to automatically generate content for various industries, from journalism, to real estate, to weather and sports reporting.
  • Select and organize source content, plan sentences, and prepare a system for automatic generation of original content.
  • Understand the NLG pipeline and apply the right techniques at each stage.
  • Understand the architecture of a Natural Language Generation (NLG) system.
  • Implement the most suitable algorithms and models for analysis and ordering.
  • Pull data from publicly available data sources as well as curated databases to use as material for generated text.
  • Replace manual and laborious writing processes with computer-generated, automated content creation.
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Provisional Upcoming Courses (Contact Us For More Information)

Advanced Techniques in Natural Language Generation (NLG)

2025-06-16 09:30
14 hours
Online

Python for Natural Language Generation (NLG)

2025-06-30 09:30
21 hours
Online

Python for Natural Language Generation (NLG)

2025-07-14 09:30
21 hours
Online

Text Summarization and Content Generation with AI (NLG)

2025-07-28 09:30
21 hours
Online

AI-Driven NLG for Chatbots and Virtual Assistants

2025-08-11 09:30
21 hours
Online

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