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CODE: NAI05
DURATION: 3 Days | 5 Days | 10 Days
CERTIFICATIONS: CPD
This course introduces participants to the powerful capabilities of transformer-based models in Natural Language Processing (NLP). Participants will explore how models like BERT, GPT, RoBERTa, and T5 work, and how to apply them to real-world tasks such as text classification, question answering, summarization, and translation. Using popular libraries like Hugging Face Transformers and tools such as PyTorch or TensorFlow, participants will gain the skills required in fine-tuning pre-trained models and deploying NLP solutions.
This course is available in the following formats:
Virtual
Classroom
Request this course in a different delivery format.
Course Outcomes
Delegates will gain the knowledge and skills to:
Understand the architecture and mechanics of transformer models.
Apply pre-trained models to NLP tasks like sentiment analysis, summarization, and Q&A.
Fine-tune transformer models for domain-specific applications.
Use Hugging Face Transformers library for training and deployment.
Handle large datasets and tokenization for NLP tasks.
Evaluate model performance and optimize output quality.
Implement best practices in responsible and ethical use of LLMs.
Integrate transformer models into production NLP pipelines.
At the end of this course, you’ll understand:
Data scientists, machine learning engineers, NLP practitioners, AI researchers, and developers looking who are into building and deploying advanced NLP applications will need this course. It is also beneficial for professionals transitioning into AI or exploring the capabilities of state-of-the-art language models. Basic knowledge of Python and machine learning is recommended.
✓ Modern facilities
✓ Course materials and certificate
✓ Accredited international trainers
✓ Training materials and workbook
✓ Access to online resources
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