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所在平台: Udemy |
课程主页: https://www.udemy.com/course/create-and-execute-successful-machine-learning-programs/
课程评论：没有评论
Coursera 课程总结：创建和执行成功的机器学习 (ML) 项目 本课程面向企业领导者，旨在全面介绍人工智能 (AI) 和机器学习 (ML) 的概念，并列举了 AI/ML 在各行各业中的实际商业应用。 **第一部分：AI/ML 战略的基石** 本部分侧重于为企业构建成功的 AI/ML 战略奠定基础。关键考虑因素包括： * **商业价值：** 明确 AI/ML 项目如何为企业带来可衡量的价值。 * **历史数据可用性：** 评估用于训练模型所需历史数据的质量和数量。 * **生产可行性/路径：** 规划项目如何从概念走向实际部署和生产环境。 我们将通过 foundational strategic pillars（基础战略支柱）来帮助定义完整的战略，并深入探讨在实施 AI/ML 时需要考虑的关键因素。 **第二部分：管理 ML 项目的挑战与负责任 AI** 本部分将探讨在实施 ML 项目过程中可能遇到的具体挑战，以及应对这些不确定性的机制。这包括： * **耗时的探索性数据分析 (EDA)：** 如何高效地进行数据探索和理解。 * **范围的调整：** 在数据分析过程中，根据对数据的更深入理解，灵活调整项目范围。 * **风险管理框架：** 引入一个风险管理框架，用于量化风险及其影响，并明确负责监督的业务部门。 此外，本课程将重点关注“负责任 AI (Responsible AI)”，强调其作为任何涉及人类的 AI/ML 应用的 foundational part（根本部分）。企业领导者有责任确保其面向客户的 ML 模型公平、无偏见，并能够解释其做出的任何决策。 本课程将帮助您掌握制定、实施和管理成功的 AI/ML 项目的能力，并强调在整个过程中对道德和责任的承担。
This course summarizes Artificial Intelligence (AI) and Machine Learning (ML) for business leaders and lists ways in which AI/ML is used in business across several industries today.In the first part, the course discusses the foundations of setting up a successful AI/ML strategy in the enterprise, considering business value, availability of historical data, and feasibility or path to production. We will use foundational strategic pillars to help define a complete strategy and look at the factors that we need to consider when implementing AI/ML.In the second part, we will look at some mechanisms to manage the specific challenges when implementing ML, given the unknown we are facing in these types of programs, such as a possible time consuming Exploratory Data Analysis, a pivot in scope as we understand the data better, and so forth.We also propose a risk management framework that quantifies risks and impacts, together with an overseeing business unit. In this context, we will focus on understanding Responsible AI and how it is a foundational part of any AI/ML use case that affects people in any way. It is the responsibility of business leaders to ensure the ML models they shepherd in front of their customers are fair and unbiased, and any decision taken can be explained.
