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所在平台: Udemy |
课程主页: https://www.udemy.com/course/ai-for-business-intelligence-data-development-with-ai/
课程评论：没有评论
**课程名称：** 商业智能数据开发中的人工智能 **课程概述：** 本课程专为数据专业人士设计，旨在教授如何利用人工智能（AI）来增强商业智能（BI）和数据开发解决方案。您将学习如何弥合数据与业务需求之间的差距，理解BI背景下的数据生命周期，并掌握GitHub Copilot和Google Gemini Code Assist等AI驱动的代码辅助工具。通过提高效率，改善代码质量，并利用AI的力量更快地交付数据驱动的洞察。课程包含动手练习和实际案例。 **课程内容涵盖：** * 数据与业务的连接 * 商业智能与数据生命周期 * AI代码辅助在数据专业领域的作用 * 数据与分析工具 * 提示工程基础 * Copilot & Gemini 代码辅助的使用 * AI在数据开发中的应用场景： * 需求收集 * 代码生成 * 测试 * 数据分析 * 可视化 **您将学到：** * 提示工程基础知识 * 负责任的AI实践 * AI在数据开发中的实际应用（包括需求收集、代码生成、测试、分析和可视化） * 与SQL Server，Visual Studio Code和Power BI等工具的集成 * 通过实际案例和练习，您将掌握： * 加速代码完成，减少调试时间 * 生成合成数据以进行健壮的测试和开发 * 自动化文档编写，提高代码理解度 * 在不同语言之间进行代码翻译（例如，SAS到SQL，Python） * 提取有价值的见解并提出业务建议 * 使用Kimball方法论开发数据仓库解决方案 * 创建有影响力的Power BI仪表板和报告 * 设计清晰且信息丰富的图表以进行解决方案文档 **学习目标：** 本课程将帮助您利用AI技术提升数据开发和商业智能的能力，从而更快、更有效地实现业务目标。
This comprehensive training pack equips data professionals with the skills to leverage AI for enhanced business intelligence and data development solutions. Learn how to bridge the gap between data and business needs, understand the data lifecycle within a BI context, and master AI-powered code assistance tools like GitHub Copilot and Google Gemini Code Assist. Increase your efficiency, improve code quality, and deliver data-driven insights faster with the power of AI. Includes hands-on exercises and real-world examples.This course covers: Data and Business bridging the gapBusiness Intelligence and Data LifecycleWhat is AI Code assist for Data professionalsTooling for Data and AnalyticsPrompt engineering FoundationsCo-Pilot & Gemini Code Assist usageUse Cases for AI in Data DevelopmentRequirementsExplainDocumentBuildTestInsights and AnalysisDiagramming your SolutionsWhat you will learn:Prompt engineering foundationsResponsible AI practicesPractical use cases for AI in data development (including requirements gathering, code generation, testing, analysis, and visualization), Integration with tools like SQL Server, Visual Studio Code, and Power BI. Through real-world examples and practical exercises, you'll discover how to:Accelerate code completion and reduce debugging time.Generate synthetic data for robust testing and development.Automate documentation and improve code understanding.Translate code between languages (e.g., SAS to SQL, Python).Extract valuable insights and formulate business recommendations.Develop data warehouse solutions using the Kimball methodology.Create impactful Power BI dashboards and reports.Design clear and informative diagrams for solution documentation.
