Transfer Learning and Fine-Tuning for AI Models
About this course
This specialization teaches you how to customize pretrained AI models into reliable, deployable systems using transfer learning and fine-tuning with Python, PyTorch, and Hugging Face. It is designed for developers and data scientists who want to move beyond training models from scratch and deliver AI solutions that perform in real business settings. By the end of this specialization, you will be able to: Explain how transfer learning reshapes pretrained models and transformers for new tasks Apply supervised and instruction fine-tuning in PyTorch and Hugging Face using LoRA Analyze model behavior through evaluation metrics, error analysis, and fairness auditing Build and deploy monitored inference services using FastAPI, Docker, and responsible AI practices No prior deep learning or fine-tuning experience is needed — just basic Python and foundational machine learning knowledge to get started. Join us now and begin your journey to become a fine-tuning and AI deployment expert.
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What you'll learn
- Explain how transfer learning reshapes pretrained models and transformers for new tasks
- Apply supervised and instruction fine-tuning in PyTorch and Hugging Face using LoRA
- Analyze model behavior through evaluation metrics, error analysis, and fairness auditing
- Build and deploy monitored inference services using FastAPI, Docker, and responsible AI practices
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