Model Fine-Tuning & Transfer Learning Courses

14 courses1.9M learners9 providers

Learn to adapt pre-trained AI models to your specific use cases using fine-tuning, transfer learning, LoRA, QLoRA, and parameter-efficient training techniques.

AllTransfer LearningLoRAQLoRAPEFTDomain AdaptationInstruction Tuning

Top Rated in Model Fine-Tuning & Transfer Learning

Hugging Face

Free

intermediate

NLP Course

Hugging Face

4.7(1,800)

Self-pacedintermediate

TensorFlow Developer Professional Certificate

Coursera

PyTorch for Deep Learning & Machine Learning

Udemy

4.7(9,500)

26 hoursintermediate

$12.99

All Model Fine-Tuning & Transfer Learning Courses

Hugging Face

Free

intermediate

NLP Course

Hugging Face

4.7(1,800)

Self-pacedintermediate

Generative AI with Large Language Models

Coursera

TensorFlow Developer Professional Certificate

Coursera

Stable Diffusion: Complete Guide to AI Image Generation

Udemy

PyTorch for Deep Learning & Machine Learning

Udemy

Finetuning Large Language Models

DeepLearning.AI

A Code-First Introduction to NLP

fast.ai

Intro to TensorFlow for Deep Learning

Google

Computer Vision

Kaggle

Generative AI Nanodegree

Udacity

Open-Source AI Cookbook

Hugging Face

4.5(600)

Self-pacedintermediate

Deep Learning for Computer Vision with TensorFlow

Coursera

LLMOps

DeepLearning.AI

PyTorch Essential Training: Deep Learning

LinkedIn Learning

4.5(3,200)

3 hoursintermediate

$29.99/mo

Browse Model Fine-Tuning & Transfer Learning Courses by Provider

See model fine-tuning & transfer learning courses from a specific platform.

Coursera DeepLearning.AI Google Hugging Face Kaggle LinkedIn Learning Udacity Udemy fast.ai

Frequently Asked Questions

What is fine-tuning in AI?

Fine-tuning adapts a pre-trained model to a specific task or domain by continuing training on a smaller, task-specific dataset. It leverages learned representations while customizing behavior for your use case.

What is the difference between fine-tuning and transfer learning?

Transfer learning is the broader concept of reusing knowledge from one task for another. Fine-tuning is a specific transfer learning technique where you continue training a pre-trained model on new data.

What is LoRA and why is it popular?

LoRA (Low-Rank Adaptation) enables efficient fine-tuning by training small adapter matrices instead of the full model. It dramatically reduces GPU memory requirements while achieving comparable performance to full fine-tuning.

How much data do I need for fine-tuning?

It depends on the task. Simple classification fine-tuning may need hundreds of examples, while instruction tuning typically requires thousands. Quality and diversity of data matter more than sheer volume.

Model Fine-Tuning & Transfer Learning Courses

Top Rated in Model Fine-Tuning & Transfer Learning

NLP Course

TensorFlow Developer Professional Certificate

PyTorch for Deep Learning & Machine Learning

All Model Fine-Tuning & Transfer Learning Courses

NLP Course

Generative AI with Large Language Models

TensorFlow Developer Professional Certificate

Stable Diffusion: Complete Guide to AI Image Generation

PyTorch for Deep Learning & Machine Learning

Finetuning Large Language Models

A Code-First Introduction to NLP

Intro to TensorFlow for Deep Learning

Computer Vision

Generative AI Nanodegree

Open-Source AI Cookbook

Deep Learning for Computer Vision with TensorFlow

LLMOps

PyTorch Essential Training: Deep Learning

Browse Model Fine-Tuning & Transfer Learning Courses by Provider

Frequently Asked Questions

Related Topics

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