Quantization Courses and Certifications

Quantization for GenAI Models

95 ratings at Udemy

Unlock the power of model optimization! Learn how to apply quantization and make your GenAI models efficient with Python

• Udemy
• 2 hours 43 minutes
• On-Demand
• Paid Course

Quantization Fundamentals with Hugging Face

15 ratings at Coursera

Learn to compress and optimize generative AI models through quantization techniques, making them more efficient and accessible for various devices while minimizing performance loss.

• Coursera
• 1 hour 30 minutes
• On-Demand
• Paid Course

Quantization in Depth

Build and customize linear quantization methods to compress model weights, balance performance and space tradeoffs, and implement techniques for 8-bit and 2-bit quantization in PyTorch.

• Coursera
• 1 hour 30 minutes
• On-Demand
• Paid Course

TensorFlow

TensorFlow Model Optimization - Quantization and Pruning

Explore TensorFlow model optimization techniques like quantization and pruning to enhance performance, reduce resource usage, and improve efficiency in machine learning applications.

• YouTube
• 41 minutes
• On-Demand
• Free Video

MIT HAN Lab

Quantization for Efficient Machine Learning - Part I - Lecture 5

Explore quantization techniques for efficient machine learning, covering fundamental concepts and practical applications in neural network optimization.

• YouTube
• 1 hour 15 minutes
• On-Demand
• Free Video

Nvidia

Inference and Quantization for AI - Session 3

Explore quantized inference, TensorRT 5, and TensorFlow integration for AI model optimization. Learn about NVIDIA's inference server and techniques to improve model efficiency and performance.

• YouTube
• 41 minutes
• On-Demand
• Free Video

MIT HAN Lab

AWQ for LLM Quantization - Efficient Inference Framework for Large Language Models

Explore Activation-aware Weight Quantization (AWQ) for efficient large language model deployment, reducing memory requirements while preserving performance across domains and modalities.

• YouTube
• 21 minutes
• On-Demand
• Free Video

MIT HAN Lab

Quantization for Efficient Machine Learning - Part II

Explore advanced quantization techniques for efficient machine learning, including post-training and quantization-aware training methods.

• YouTube
• 1 hour 11 minutes
• On-Demand
• Free Video

MIT HAN Lab

EfficientML.ai: Quantization Part II - Lecture 6

Explore advanced quantization techniques for efficient machine learning, including Rooney quantization, scaling factors, and fine-tuning strategies.

• YouTube
• 1 hour 15 minutes
• On-Demand
• Free Video

MIT HAN Lab

EfficientML.ai - Quantization Part I - Lecture 5

Explore quantization techniques for efficient machine learning, focusing on part I of the topic in this MIT lecture by Prof. Song Han.

• YouTube
• 1 hour 15 minutes
• On-Demand
• Free Video

MIT HAN Lab

Quantization in Neural Networks - Lecture 5

Explore neural network quantization, including numeric data types, K-means-based quantization, and linear quantization for efficient deep learning on resource-constrained devices.

• YouTube
• 1 hour 12 minutes
• On-Demand
• Free Video

Trelis Research

Double Inference Speed with AWQ Quantization

Boost inference speed and accuracy using AWQ quantization. Deploy Llama 2 70B server, set up chat-UI, and run AWQ in Colab. Explore quantization techniques for language models, including GPTQ. Gain pro tips for implementation.

• YouTube
• 23 minutes
• On-Demand
• Free Video

AI Bites

Quantization in Deep Learning: Types, Algorithms, and Implementation

Explore quantization techniques in deep learning, from uniform to non-uniform approaches, and learn practical implementation strategies for optimizing large-scale neural networks.

• YouTube
• 13 minutes
• On-Demand
• Free Video

Discover AI

RTX PRO 6000 with 4-bit AI Models - Quantization Breaks

Uncover why 4-bit AI quantization fails complex reasoning tasks, causing 30% trust collapse and hidden energy costs despite hardware advances like RTX PRO 6000.

• YouTube
• 13 minutes
• On-Demand
• Free Video

tinyML

Extremely Low-Bit Quantization for Transformers - tinyML Asia 2021

Explore extremely low-bit quantization techniques for Transformers, focusing on mixed precision strategies to optimize deployment on resource-limited devices without compromising accuracy.

• YouTube
• 28 minutes
• On-Demand
• Free Video