This course covers the challenges and solutions in industry-scale data and AI systems. The learning outcomes include understanding data and AI technologies, big data infrastructure, AI engineering, recommendation systems, and business decision-making. The course teaches skills such as working with data warehouses, natural language queries, AI training procedures, and distributed computation. The teaching method involves discussing real-world examples and case studies. The intended audience for this course includes data scientists, AI engineers, and professionals working with large-scale data and AI systems.
Challenges and Solutions in Industry Scale Data and AI Systems - Yangqing Jia
Association for Computing Machinery (ACM) via YouTube
Overview
Syllabus
Intro
About Alibaba
Global Shopping Festival
Data and AI Technologies
Big Data
Big Data Infrastructure
Holographs
Autonomous Computing
Eagle
Data warehouse and data lake
Natural language query
Big data needs
BI and AI
AI Engineering
AI Training Procedures
Distributed Computation
M6 Pretrained Model
M6 for Design
Platform for AI
Recommendation Systems
AI Recommendation
Digital Twin
Business Decision Making
Conventional ATC
Summary
Audience Questions
Taught by
Association for Computing Machinery (ACM)
