Fine-tuning Your Own GPT Model

This technical course walks through preparing datasets, fine-tuning a GPT-style model, evaluating performance, and deploying it for specialised tasks. You will learn data cleaning and formatting, supervised fine-tuning strategies, validation metrics, and monitoring for drift and safety. Practical labs include small-domain fine-tuning examples and deployment patterns to integrate models into services with monitoring and rollback mechanisms.

• Skills you’ll learn: dataset prep, fine-tuning workflows, evaluation metrics, deployment patterns, monitoring and safety.

Certificate: Certificate of completion provided upon finishing the course.

Requirements

• Familiarity with ML tooling; compute resources and a prepared dataset.

Who this course is for

• ML engineers; data scientists; prompt engineers.

Benefits

• Prepare and clean datasets; fine-tune models; evaluate performance; deploy and monitor the fine-tuned model.