Parameter-Efficient Fine-Tuning Courses and Certifications

Coursera

Fine-tuning Text Models with PEFT

Fine-tune large language models on consumer GPUs: implement QLoRA and LoRA, tune learning rates, batch sizes and rank, and evaluate with perplexity, BLEU, ROUGE and BERTScore.

• Coursera
• 4 weeks, 2 hours a week
• Self-Paced
• Paid Course

Pragmatic AI Labs

Advanced Fine-Tuning in Rust

Fine-tune 7-billion-parameter models on a laptop GPU with QLoRA: trace transformer internals, configure LoRA rank, build AST-extracted corpora, and publish datasets to Hugging Face.

• Coursera
• 4 weeks, 1 hour a week
• Self-Paced
• Paid Course

Board Infinity

Fine-Tune Your Own LLM: LoRA, QLoRA & PEFT

Fine-tune open-source LLMs on consumer GPUs with LoRA, QLoRA, and PEFT, prepare chat datasets, apply DPO or ORPO, and deploy with vLLM or Hugging Face Inference Endpoints.

• Coursera
• 5 weeks, 2 hours a week
• Self-Paced
• Paid Course

Sam Witteveen

Fine-Tuning LLMs with PEFT and LoRA

1 rating

Learn parameter-efficient fine-tuning of decoder-style GPT models with PEFT and LoRA, including a Hugging Face code walkthrough.

• YouTube
• 16 minutes
• Self-Paced
• Free Video

AI Bites

Fine-tuning Gemma Models with PEFT and LoRA Using HuggingFace Datasets

Master parameter-efficient fine-tuning techniques for Gemma 2B model using PEFT and LoRA, with hands-on code implementation and custom dataset creation for optimized model training.

• YouTube
• 24 minutes
• Self-Paced
• Free Video

Venelin Valkov

Fine-Tuning Alpaca- Train Alpaca LoRa for Sentiment Analysis on a Custom Dataset

Fine-tune Llama 7B with Alpaca LoRA to classify sentiment in a custom Bitcoin-tweet dataset.

• YouTube
• 34 minutes
• Self-Paced
• Free Video

Fine-Tuning with Llama 3

405 ratings at DataCamp

Fine-tuning the Llama model This course provides a comprehensive guide to preparing and working with Llama models.

• DataCamp
• 2 hours
• Self-Paced
• Free Trial Available

AI Bites

LoRA: Low-Rank Adaptation for Parameter-Efficient Large Language Model Fine-Tuning

Discover how LoRA enables efficient fine-tuning of large language models through low-rank adaptation, from fundamental concepts to practical implementation in transformer architectures.

• YouTube
• 11 minutes
• Self-Paced
• Free Video

Google DeepMind: Fine-Tune Your Model

17 ratings at DataCamp

Fine-tune language models: reformat a dataset into question-and-answer flashcards, run full-parameter training, apply LoRA to Gemma3-1B, and weigh SFT limits and governance responses.

• DataCamp
• 8 hours
• Self-Paced
• Free Trial Available

Generative AI - Adapting LLMs with Parameter-Efficient Fine-Tuning - Lecture 10

Master parameter-efficient fine-tuning techniques for adapting large language models, covering GPT versions, training data nuances, and instruction tuning methods.

• YouTube
• 1 hour 18 minutes
• Self-Paced
• Free Video

Data Centric

Fine-tuning LLMs Without Maxing Out Your GPU - LoRA for Parameter-Efficient Training

Discover parameter-efficient fine-tuning of large language models using LoRA. Learn to classify consumer finance complaints with RoBERTa on Google Colab's V100 GPU.

• YouTube
• 47 minutes
• Self-Paced
• Free Video

Toronto Machine Learning Series (TMLS)

Prompt Optimization and Parameter Efficient Fine Tuning for Large Language Models

Explore state-of-the-art prompt optimization techniques and parameter efficient fine-tuning methods for large language models to enhance performance on various tasks.

• YouTube
• 28 minutes
• Self-Paced
• Free Video

CodeEmporium

LoRA - Low Rank Adaptation for Parameter Efficient Fine-Tuning

Dive into parameter-efficient fine-tuning with LoRA, exploring low-rank matrices, adapters, and techniques to optimize neural network storage and performance while maintaining accuracy.

• YouTube
• 29 minutes
• Self-Paced
• Free Video

LLMs Mastery: Complete Guide to Transformers & Generative AI

9277 ratings at Udemy

Build and fine-tune your own LLMs: Transformers, Hugging Face, PEFT, LoRA, QLoRA, RLHF, quantisation, DeepSpeed

• Udemy
• 7 hours 30 minutes
• Self-Paced
• Paid Course

Generative AI Engineering and Fine-Tuning Transformers

119 ratings at Coursera

Fine-tune large language models with Hugging Face and PyTorch: load and pretrain transformers, then apply PEFT, adapters, LoRA, QLoRA, quantization, and soft prompts.

• Coursera
• 2 weeks, 4 hours a week
• Self-Paced
• Paid Course