Master the complete workflow for fine-tuning transformer models using the Hugging Face ecosystem. This hands-on course takes you from navigating the Hugging Face Hub to deploying production-ready models.You'll start by learning to discover, evaluate, and select models and datasets from the Hub's vast repository. Then you'll build practical skills in loading and preprocessing data, including streaming techniques for datasets too large to fit in memory.The core of the course focuses on fine-tuning transformers using the Trainer API. You'll implement custom callbacks, configure training optimizations like mixed precision, and develop comprehensive evaluation pipelines with metrics including accuracy, F1, precision, and recall.The capstone project ties everything together: you'll build an end-to-end sentiment analysis system, from data preprocessing and augmentation through training, evaluation, and publishing your model to Hugging Face Hub with professional documentation.By course end, you'll have hands-on experience with the same tools and workflows used by ML teams at leading organizations, plus a published model in your portfolio.

Fine-Tuning Transformers with Hugging Face

Fine-Tuning Transformers with Hugging Face
This course is part of Next-Gen AI Development with Hugging Face Specialization


Instructors: Noah Gift
Access provided by PALC Dev
Recommended experience
What you'll learn
Navigate the Hugging Face Hub to discover, evaluate, and select models and datasets based on task requirements, licensing, and technical constraints.
Skills you'll gain
Details to know

Add to your LinkedIn profile
2 assignments
February 2026
See how employees at top companies are mastering in-demand skills

Build your subject-matter expertise
- 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 are 4 modules in this course
Build robust data pipelines for transformer fine-tuning. Load datasets from multiple sources, apply transformations efficiently, and handle real-world data challenges like class imbalance.
What's included
17 videos10 readings1 assignment
Fine-tune transformer models using the Trainer API. Configure training parameters, optimize performance with mixed precision, and monitor progress with callbacks and logging.
What's included
15 videos9 readings
Share fine-tuned models with the community. Publish to Hugging Face Hub with proper documentation, and automate the training-to-deployment pipeline with GitHub Actions.
What's included
11 videos9 readings
Build an end-to-end sentiment analysis system that fine-tunes a transformer model on custom data and deploys it to Hugging Face Hub. This capstone demonstrates mastery of the complete fine-tuning workflow.
What's included
1 reading1 assignment
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
Offered by
Why people choose Coursera for their career

Felipe M.

Jennifer J.

Larry W.

Chaitanya A.
Explore more from Computer Science

Pragmatic AI Labs

DeepLearning.AI

Simplilearn


