This intermediate-level course is designed for database professionals, ML engineers, and AI practitioners who need to build and maintain high-performance LLM systems. In the world of large-scale AI, slow queries and inefficient search can bring a system to its knees. This course provides the critical skills to prevent that, focusing on practical database and vector search optimization techniques.
Optimize SQL and Vector Search Parameters
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您将学到什么
Optimize SQL queries and vector search for high-performance LLM systems and implement comprehensive benchmarking for production retrieval systems.
您将获得的技能
要了解的详细信息
了解顶级公司的员工如何掌握热门技能
该课程共有3个模块
This module provides essential techniques for writing secure and efficient SQL to diagnose performance issues in production systems. You will learn why query optimization is critical, what parameterized queries are, and how to construct them to retrieve performance data safely. You will conclude by applying these skills in a hands-on lab.
涵盖的内容
1个视频1篇阅读材料1个作业1个非评分实验室
This module focuses on the core challenge of vector search: balancing accuracy and speed. You will learn why this trade-off is fundamental, what key ANN algorithm parameters control it, and how to methodically tune them. You will apply this knowledge in a lab to find the optimal balance for a given use case.
涵盖的内容
2个视频1篇阅读材料1个作业1个非评分实验室
In this module, you will learn how to build a systematic framework for performance testing. You will discover why continuous benchmarking is superior to one-off tests, what key metrics to measure, and how to create an automated suite to ensure your system remains performant over time.
涵盖的内容
1个视频1篇阅读材料2个作业1个非评分实验室
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