Natural Language Generation (NLG) Training in Maryland
Online or onsite, instructor-led live Natural Language Generation (NLG) training courses demonstrate through interactive hands-on practice how to use NLG techniques and tools to automatically generate human-like text from data, enabling the creation of reports, summaries, and content across various applications.
NLG training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Maryland onsite live Natural Language Generation (NLG) trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
MD, Baltimore - Legg Mason Tower
100 International Drive 23rd Floor, Baltimore, United States, 21202
A state-of-the-art, 24-story glass skyscraper that sits on the edge of Baltimore's Inner Harbor is the signature home of the Legg Mason office. It's located on the 23rd floor of this class-A office development, which is designed by world-renowned architects and boasts panoramic views. The office space benefits from the tower's ‘green' LEED credentials, proximity to Interstate 83 and excellent onsite amenities. Inner Harbor is the chief commercial and tourist destination in Baltimore and part of the Downtown area - the base for many key businesses.
This instructor-led, live training in Maryland (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.
This instructor-led, live training in Maryland (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.
This instructor-led, live training in Maryland (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.
This instructor-led, live training in Maryland (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.
In this instructor-led, live training in Maryland, 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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