Quantization Courses and Certifications

MIT HAN Lab

EfficientML.ai: Quantization Part II - Lecture 6

Explore advanced quantization techniques for efficient machine learning, covering post-training and quantization-aware training methods to optimize model performance.

• YouTube
• 1 hour 9 minutes
• On-Demand
• Free Video

MIT HAN Lab

EfficientML.ai - Quantization Part II - Lecture 6

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

• YouTube
• 1 hour 9 minutes
• On-Demand
• Free Video

MIT HAN Lab

EfficientML.ai - Quantization Part I - Lecture 5

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

• YouTube
• 1 hour 7 minutes
• On-Demand
• Free Video

MIT HAN Lab

EfficientML.ai - Quantization Part I - Lecture 5

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

• YouTube
• 1 hour 7 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

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

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

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

Stanford Seminar - Neural Networks on Chip Design from the User Perspective

We will briefly review our past effort on Deep learning Processing Unit (DPU) design on FPGA in Tsinghua and Deephi, and then talk about some features, i.e. interrupt and virtualization, we are trying to introduce into the accelerators from the user's pe…

• YouTube
• 58 minutes
• On-Demand
• Free Online Course

Lossy Compression Basics and Quantization - Lecture 11

Explore lossy compression fundamentals and quantization techniques in this Stanford lecture, covering essential concepts for efficient data reduction in various applications.

• YouTube
• 1 hour 24 minutes
• On-Demand
• Free Video

Llama for Python Programmers

12 ratings at Coursera

Learn to leverage Llama 2 LLM in Python applications. Explore open-source LLMs, quantization, prompting techniques, and model variants. Gain hands-on skills to integrate generative AI into your work.

• Coursera
• 5 hours 40 minutes
• On-Demand
• Free Online Course (Audit)

Digital Signal Processing 1: Basic Concepts and Algorithms

596 ratings at Coursera

Digital Signal Processing is the branch of engineering that, in the space of just a few decades, has enabled unprecedented levels of interpersonal communication and of on-demand entertainment.

• Coursera
• 1 day 4 hours 44 minutes
• On-Demand
• Free Online Course (Audit)

Computer Vision for Embedded Systems

Learn about constraints and reducing resource requirements for computer vision on embedded systems.

• edX
• 5 weeks, 7-8 hours a week
• On-Demand
• Free Online Course (Audit)