Generative AI Engineering and Fine-Tuning Transformers
Completed by Kun Yu Cheung
January 25, 2026
8 hours (approximately)
Kun Yu Cheung's account is verified. Coursera certifies their successful completion of Generative AI Engineering and Fine-Tuning Transformers
What you will learn
Sought-after, job-ready skills businesses need for working with transformer-based LLMs in generative AI engineering
How to perform parameter-efficient fine-tuning (PEFT) using methods like LoRA and QLoRA to optimize model training
How to use pretrained transformer models for language tasks and fine-tune them for specific downstream applications
How to load models, run inference, and train models using the Hugging Face and PyTorch frameworks
Skills you will gain
- Category: Model Training
- Category: Prompt Engineering
- Category: Generative AI
- Category: Model Optimization
- Category: Large Language Modeling
- Category: Fine-tuning
- Category: PyTorch (Machine Learning Library)
- Category: Generative Model Architectures
