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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-science-for-business-leaders-machine-learning-defined/
课程评论：没有评论
课程名称：商业领导者的数据科学：机器学习基础 概述：机器学习是一项商业领导者应掌握的能力，以便从数据中提取价值。尽管存在许多夸大的说法，但现代数据科学技术的应用确实能够带来显著的进步或竞争优势。无论是构建还是购买“人工智能驱动”的解决方案，考虑贵组织如何利用机器学习都至关重要。本课程不涉及编码或复杂的数学内容，也不是实践课程。我们旨在用简单的英语解释您需要了解的所有基本概念。课程分为五个关键部分： 第一部分：机器学习、深度学习与人工智能的定义 这一部分的使命是让您对机器学习有一个坚实的理解。掌握这些概念和术语是您利用它们作为能力的第一步，我们将通过基本示例来巩固理解。 第二部分：识别用例 厌倦了听到相同的机器学习用例？不确定机器学习是否适用于您？在这里获取专家建议，了解如何在您的组织中发现机器学习机会。 第三部分：资格认定用例 一旦您确定了机器学习的使用案例，您需要测量和评估该机会。如何分析和量化机器学习驱动解决方案的优势？您不需要成为数据科学家就能从这一讨论中受益。这对负责优化业务流程的商业领导者来说是必要的知识。 第四部分：构建机器学习能力 有关构建/购买机器学习和人工智能解决方案的关键考虑和建议。 第五部分：战略要点 机器学习如何长期改变商业环境的展望，以及您现在可以采取哪些措施以确保贵组织能够在未来利用机器学习。 总的来说，本课程旨在为商业领导者提供关于机器学习的基本认识，使他们能够更好地在工作中应用相关技术。
Machine learning is a capability that business leaders should grasp if they want to extract value from data. There's a lot of hype; but there's some truth: the use of modern data science techniques could translate to a leap forward in progress or a significant competitive advantage. Whether your are building or buying "AI-powered" solutions, you should consider how your organization could benefit from machine learning. No coding or complex math. This is not a hands-on course. We set out to explain all of the fundamental concepts you'll need in plain English. This course is broken into 5 key parts:Part 1: Models, Machine Learning, Deep Learning, & Artificial Intelligence DefinedThis part has a simple mission: to give you a solid understanding of what Machine Learning is. Mastering the concepts and the terminology is your first step to leveraging them as a capability. We walk through basic examples to solidify understanding.Part 2: Identifying Use CasesTired of hearing about the same 5 uses for machine learning over and over? Not sure if ML even applies to you? Take some expert advice on how you can discover ML opportunities in *your* organization. Part 3: Qualifying Use CasesOnce you've identified a use for ML, you'll need to measure and qualify that opportunity. How do you analyze and quantify the advantage of an ML-driven solution? You do not need to be a data scientist to benefit from this discussion on measurement. Essential knowledge for business leaders who are responsible for optimizing a business process.Part 4: Building an ML CompetencyKey considerations and tips on building / buying ML and AI solutions. Part 5: Strategic Take-awaysA view on how ML changes the landscape over the long term; and discussion of things you can do *now* to ensure your organization is ready to take advantage of machine learning in the future.
