中As Generative AI transforms industries, data professionals must evolve too. This intermediate-level course empowers you to master the modern data management techniques essential for building scalable, ethical, and intelligent AI systems.
Advanced Data Techniques for Enterprise AI Systems
您将学到什么
Explain the foundational role of data management, security, and architecture in enterprise AI.
Implement cross-platform compatibility across AI models, datasets, and systems.
Apply vector database and embedding techniques to manage unstructured data.
Build unified data architectures using Iceberg, Delta, and DuckLake.
您将获得的技能
- Data Management
- Data Processing
- Semantic Web
- Data Architecture
- Data Storage
- Real Time Data
- Data Loss Prevention
- Data Ethics
- Docker (Software)
- Data Security
- Metadata Management
- Data Strategy
- Data Store
- Responsible AI
- Agentic systems
- Interoperability
- Machine Learning
- Data Governance
- Generative AI Agents
- Large Language Modeling
要了解的详细信息
可分享的证书
添加到您的领英档案
最近已更新！
September 2025
作业
12 项作业
授课语言：英语（English）
了解顶级公司的员工如何掌握热门技能
积累特定领域的专业知识
本课程是 Modern Data Strategy for Enterprise Generative AI 专项课程 专项课程的一部分
在注册此课程时，您还会同时注册此专项课程。
- 向行业专家学习新概念
- 获得对主题或工具的基础理解
- 通过实践项目培养工作相关技能
- 获得可共享的职业证书
该课程共有6个模块
Understand the pillars of modern data strategy—management, frameworks, and governance. Learn how to secure data using encryption, access control, and ISO standards.
涵盖的内容
4个视频2篇阅读材料2个作业1个插件
Master interoperability across clouds and platforms using Docker, Kubernetes, APIs, and the SECURE framework to build scalable, resilient AI systems.
涵盖的内容
5个视频1篇阅读材料2个作业1个非评分实验室
Organize and retrieve data efficiently using metadata tagging. Learn how tagging powers Retrieval-Augmented Generation (RAG) and enhances AI accuracy.
涵盖的内容
6个视频2个作业1个非评分实验室1个插件
Explore vector databases for semantic and multimodal search. Learn about indexing strategies, ANN algorithms, and hardware acceleration for real-time AI.
涵盖的内容
8个视频4篇阅读材料2个作业1个非评分实验室1个插件
Dive into data lakes, warehouses, and lakehouses. Use tools like DuckLake and Databricks to unify structured and unstructured data for Gen AI.
涵盖的内容
8个视频2篇阅读材料2个作业1个非评分实验室1个插件
Apply governance frameworks like DAMA-DMBOK and EDM. Implement Explainable AI, Zero Trust Architecture, and Data Loss Prevention for secure, ethical AI systems.
涵盖的内容
6个视频1篇阅读材料2个作业1个插件
获得职业证书
将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。
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常见问题
This course provides foundational knowledge about data frameworks that support generative AI applications. It's important because even the most advanced AI models will produce unreliable results without properly structured, high-quality data foundations.
This course is designed for data professionals, AI leaders, and anyone responsible for implementing or overseeing generative AI initiatives who wants to understand how data strategy impacts AI performance.
You'll be able to design appropriate data frameworks for AI applications, implement effective data taxonomies, apply governance principles to AI data, and ensure your organization's data strategy supports reliable generative AI development.
更多问题
提供助学金，