Natural Language Generation (NLG) Training in Cambridge

This instructor-led, live training in Cambridge (online or onsite) is aimed at intermediate-level professionals who wish to develop practical skills in utilizing Natural Language Generation (NLG) for automating text summarization and content generation for government.

By the end of this training, participants will be able to:

• Comprehend the fundamental principles of NLG as they apply to text summarization and content generation.
• Implement NLG models to effectively summarize large documents and articles for government use.
• Utilize pre-trained NLG models, such as GPT, for creating relevant content.
• Apply advanced techniques to fine-tune NLG models for specific content generation tasks within the public sector.

This instructor-led, live training in Cambridge (online or onsite) is designed for advanced-level professionals who aim to master AI-driven natural language generation (NLG) techniques for chatbot and virtual assistant applications.

By the end of this training, participants will be able to:

• Understand the fundamental principles of NLG as they apply to conversational artificial intelligence.
• Utilize deep learning methods to improve chatbot dialogue generation.
• Incorporate cutting-edge NLG models, such as GPT-3, into chatbot frameworks for government use.
• Implement contextual AI to enhance the coherence and fluidity of conversational interactions.

This instructor-led, live training in Cambridge (online or onsite) is aimed at intermediate-level professionals who wish to enhance their skills in generating high-quality, human-like text using advanced natural language generation (NLG) methods for government applications.

By the end of this training, participants will be able to:

• Understand advanced techniques for generating natural language text for government use.
• Implement and fine-tune transformer-based models for NLG in public sector contexts.
• Optimize NLG outputs for fluency, coherence, and relevance in government communications.
• Evaluate the quality of generated text using both automated and human metrics to ensure alignment with public sector standards.

This instructor-led, live training in Cambridge (online or onsite) is designed for government professionals at the beginner level who wish to gain a foundational understanding of Natural Language Generation (NLG) and its role in artificial intelligence and content generation for government.

By the end of this training, participants will be able to:

• Comprehend the core principles of Natural Language Generation.
• Examine the diverse applications of NLG across various sectors, including those relevant to public sector workflows.
• Acquire basic techniques for generating human-like text using AI tools tailored for government use.
• Utilize Python libraries and models to create text that aligns with governmental standards and requirements.

In this instructor-led, live training in Cambridge, participants will learn how to use Python to produce high-quality natural language text by building their own NLG system from scratch. Case studies relevant to public sector workflows and governance will be examined, and the concepts will be applied to hands-on lab projects for generating content tailored for government.

By the end of this training, participants will be able to:

• Utilize NLG to automatically generate content for various industries, including journalism, real estate, weather reporting, and sports, with a focus on applications for government.
• Select and organize source content, plan sentences, and prepare a system for the automatic generation of original content that aligns with public sector needs.
• Understand the NLG pipeline and apply the appropriate techniques at each stage to ensure compliance with governmental standards.
• Comprehend the architecture of a Natural Language Generation (NLG) system designed for government use.
• Implement the most suitable algorithms and models for analysis and ordering, ensuring they meet the requirements of public sector workflows.
• Pull data from publicly available data sources as well as curated databases to use as material for generated text that supports government operations.
• Replace manual and laborious writing processes with computer-generated, automated content creation that enhances efficiency and accountability in government tasks.