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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-analytics-and-artificial-intelligence-for-beginners/
课程评论：没有评论
课程名称：初学者的数据分析与人工智能 课程概述： 本课程提供可下载的练习文件，帮助学生实践。丰富的数据存储只有在你能够有效搜索、排序、分析和展示其中的数据时才有价值。此入门级课程将为学生提供有关数据分析理论和实践的广泛概述，以及人工智能（AI）如何在其中发挥作用。 讲师将从数据分析的简要历史开始，随后讨论数据仓库、数据挖掘、商业智能、机器学习以及其他新兴的AI技术，以便理解海量数据。学生将学习数据的捕捉、清洗、分析及如何在商业智能仪表盘上展示数据，以吸引和说服观众。正如福尔摩斯所说：“在没有数据之前，理论是一种致命的错误”。 无论你是考虑将分析作为职业选择，还是希望更好地理解你在职业圈中日益频繁遇到的术语，本课程都将为你提供所需的基础知识。该课程包括3小时的教学视频和基于实践的评估，帮助学生模拟在当今复杂工作环境中，成功所需的真实数据分析场景。 学生将获得以下内容： - 数据分析的历史简述，从中世纪统计学到谷歌和微软等公司发展出的先进技术。 - 数据存储的不断增长及处理“海量数据”的挑战。 - 数据挖掘的理解，包括不同方法及领先者。 - 商业智能的两部分讨论，包括合理仪表盘设计和数据展示原则。 - 四种分析类型（诊断性分析、描述性分析、预测性分析和规范性分析）之间的关键区别，以及它们如何相互关联并在各行业中应用。 - 特定的分析过程和模型概述。 - 人工智能的首次探索，包括其演变、功能以及对当前企业的帮助。 - 机器学习的探讨，包括如何通过数据学习、识别模式和做出决策。 - 深度学习技术的调查，包括多种神经网络。 - 最重要的机器学习数据建模技术概述。 - 对当前及未来分析和AI领域的实际评估，包括其巨大的潜力和潜在风险。 - 对这些主题的继续学习资源。 课程包含： - 3小时的视频教程 - 20个独立的视频讲座 - 随堂课程和练习文件 - 完成证书
**This course includes downloadable exercise files to work with**The richest data store is only as good as your ability to search, sort, analyze, and present the data within it. This introductory-level course will give students a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it.Your instructor will begin with a brief history of data analytics and then proceed into discussions of data warehouses, data mining, business intelligence, machine learning, and other emerging AI techniques to make sense of big data.Students will learn how data is captured, cleansed, analyzed, and presented on business intelligence dashboards that captivate and persuade an audience. "It is a capital mistake to theorize before one has data," Sherlock Holmes once said.Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles, this course will give you the foundation you are looking for.This program includes 3 hours of instruction and a practice-based assessment, which will help students simulate real-world data analytics scenarios that are critical for success in today's increasingly complex workplace.Students will gain:A brief overview of the history of analyzing data, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.A look at data stores, which are growing exponentially, and the challenges of wrangling "big data."Understanding of data mining-what it entails, different approaches, and who's leading the way.A two-part discussion of business intelligence, including the principles of sound dashboard design and data presentation.The key differences between the four types of analytics-diagnostic, descriptive, predictive, and prescriptive-and how they relate to and build upon each other, and how they apply to various industries.An overview of specific analytics processes and models.A first look at AI, its evolution, its functions, and what it can do for businesses today.An exploration of machine learning-how systems can learn from data, identify patterns, and make decisions with little human intervention.A survey of deep learning technologies, including a variety of neural networks.An overview of the most important machine learning data modeling techniquesA practical and honest appraisal of the analytics and AI landscape today and moving forward, including the tremendous promise and the potential pitfalls.Resources for continued study on these topics.This course includes:3 hours of video tutorials20 individual video lecturesCourse and Exercise files to follow alongCertificate of completion
