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Workshop No. 02

Building Transformer-Based Natural Language Processing Applications

Dr. Yahya Al-Balawi. College of Computer Science and Engineering, Taibah University.

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Overview

Natural Language Processing has changed rapidly with the rise of Transformer-based models. These models are now widely used in applications such as text classification, question answering, information extraction, summarization, and conversational AI.

This NVIDIA Deep Learning Institute workshop introduces participants to the main ideas behind Transformer-based NLP and gives them practical experience in building and deploying language applications. The session combines conceptual explanation with hands-on exercises using modern deep learning tools and GPU-accelerated computing.

Participants will learn how Transformer models process language, how pre-trained models can be adapted to different NLP tasks, and how these models can be prepared for practical deployment.

Workshop Highlights

  • Understand Transformer architectures, including attention mechanisms and contextual language representation.
  • Use pre-trained language models such as BERT and apply them to practical NLP tasks.
  • Build NLP applications through hands-on work with text classification, named-entity recognition, and question answering.
  • Explore self-supervised learning and how modern language models learn from large text collections.
  • Adapt models to specific tasks by considering model selection, data requirements, performance, and domain-specific use cases.
  • Prepare and deploy NLP models using NVIDIA tools such as Triton Inference Server.

Why Attend?

This workshop is suitable for students, researchers, educators, developers, and professionals who want a practical introduction to modern NLP.

It is especially useful for participants who want to understand not only how to use AI tools, but also how language models are built, adapted, and deployed.

Certificate

Participants who successfully complete the assessment will receive an NVIDIA Deep Learning Institute certificate.