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Introduction to Transformer Models for NLP: Unit 3

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Introduction to Transformer Models for NLP: Unit 3

This course is part of Introduction to Transformer Models for NLP Specialization

Instructors: Pearson

Included with

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1 module

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

1 module

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Understand and apply the T5 model’s end-to-end transformer architecture for advanced NLP tasks.
Fine-tune and evaluate transformer models for complex applications like abstractive summarization.
Leverage Vision Transformers and build custom image captioning systems by combining vision and language models.
Deploy, share, and operationalize transformer models using modern MLOps tools and cloud frameworks.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

5 assignments

Taught in English

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This course is part of the Introduction to Transformer Models for NLP Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There is 1 module in this course

This course covers transformer models and their applications in natural language processing and computer vision. Topics include the T5 model, fine-tuning for tasks such as abstractive summarization, and the Vision Transformer. Students will learn to build an image captioning system by combining vision and language models. The course also provides practical instruction on deploying models, including MLOps practices, sharing models on HuggingFace, and cloud deployment with FastAPI. By the end of the course, students will have the knowledge and skills to implement, fine-tune, and deploy transformer models for various real-world tasks.

This module explores advanced transformer models and their applications across natural language processing and computer vision. Learners will examine the T5 model’s end-to-end architecture and cross-attention mechanism, apply and fine-tune T5 for complex NLP tasks, and discover how vision transformers extend these techniques to image processing and image captioning. The module concludes with practical strategies for deploying and sharing transformer models using MLOps principles, HuggingFace, and FastAPI, equipping students with both theoretical understanding and hands-on skills for state-of-the-art model development and deployment.

What's included

15 videos5 assignments

15 videos Total 143 minutes

Topics 1 minute
Encoders and decoders welcome: T5-s architecture 7 minutes
Cross-attention 6 minutes
Topics 0 minutes
Off the shelf results with T5 14 minutes
Using T5 for abstractive summarization 16 minutes
Topics 1 minute
Introduction to the Vision Transformer (ViT) 13 minutes
Fine-tuning an image captioning system 29 minutes
Topics 1 minute
Introduction to MLOps 17 minutes
Sharing our models on HuggingFace 17 minutes
Deploying a fine-tuned BERT model using FastAPI 18 minutes
Introduction to Transformer Models for NLP: Summary 2 minutes
Course Summary 2 minutes

5 assignments Total 150 minutes

T5 - Back to Basics Quiz 30 minutes
Hands-on T5 Quiz 30 minutes
The Vision Transformer Quiz 30 minutes
Deploying Transformer Models Quiz 30 minutes
End of Course Assessment 30 minutes

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Instructors

Pearson

268 Courses 48,983 learners

Offered by

Pearson

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Frequently asked questions

Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.