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Efficiently Serving LLMs
by Travis Addair · DeepLearning.AI
4.5(2,200 reviews)
35K+ enrolled1 hourUpdated 2024-09
What You'll Learn
Understand the fundamentals and key concepts of LLMs
Apply LLMs techniques to solve real-world problems
Understand the fundamentals and key concepts of model deployment
Apply model deployment techniques to solve real-world problems
Understand the fundamentals and key concepts of quantization
Apply quantization techniques to solve real-world problems
About This Course
Optimize LLM serving with batching, KV caching, quantization, and model parallelism for production deployments.
Curriculum
Module 1: LLMs & Model deployment6 lessons
- Introduction to LLMs
- LLMs in Practice
- Hands-on Exercise: LLMs
- Introduction to model deployment
- Model deployment in Practice
- Hands-on Exercise: Model deployment
Module 2: Quantization & Model optimization6 lessons
- Introduction to quantization
- Quantization in Practice
- Hands-on Exercise: Quantization
- Introduction to model optimization
- Model optimization in Practice
- Hands-on Exercise: Model optimization
Module 3: MLOps3 lessons
- Introduction to MLOps
- MLOps in Practice
- Hands-on Exercise: MLOps
Instructor
Travis Addair
Instructor at DeepLearning.AI
Pros & Cons
Pros
- Completely free to access
- High-quality video lectures
- Taught by Travis Addair
- Well-structured curriculum
Cons
- No certificate provided
- Requires significant prior knowledge
- Self-paced requires discipline
Free
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