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所在平台: Udemy |
课程主页: https://www.udemy.com/course/the-definitive-intro-to-big-data-science/
课程评论：没有评论
**课程名称：** 大数据科学权威入门 **课程概述：** 您是否对大数据和数据科学感兴趣？是否厌倦了那些只讲解单一工具或编程语言，却无法勾勒整体大局的课程？那么，这门课程正是您一直在寻找的！ 本课程将全面深入地探讨大数据科学的方方面面。我们将为您揭示大数据的所有构成要素，包括 NoSQL 存储、MapReduce 批处理以及 Spark 等流处理工具。更重要的是，我们将为您搭建一座通往数据科学的桥梁，涵盖监督学习和无监督学习等机器学习核心原理，以及人工智能。 我们采用直接务实的方法，为您介绍职业生涯或组织中可能遇到的所有数据方面，为您在大数据和数据科学领域打下坚实的基础，指明更深入学习特定主题的正确方向。 **讲师介绍：** Erik Tromp 教授在大数据科学领域拥有近 15 年的从业经验。他发表了超过 20 篇学术论文，以其务实的数据处理方法和在真实场景中的应用而闻名。凭借其对大数据、数据科学和数据架构的广泛理解，Erik 教授在商业领域教授这些概念已超过十年，并获得了荣誉。 首次，他决定将屡获殊荣的教学材料以数字形式提供给大众，为任何希望学习数据相关知识的人提供极具吸引力的学习机会。
Are you interested into big data? Data science? Tired of finding only courses that describe one tool or programming language but fail to set a broad standard that sketches the bigger picture? Then this course is exactly what you've been looking for!In this course we leave no stone unturned when it comes to big data science. Not only will we demystify big data in all of its aspects - NoSQL storage, batch processing using MapReduce, streaming tools like Spark - but we will also build a bridge to data science and its core principles such as supervised and unsupervised Machine Learning and Artificial Intelligence.We provide a no-nonsense approach to introduce every aspect of data you will ever encounter in your career or organization and set a strong fundament to both marry the field of big data with data science AND continue in exactly the right direction for more in-depth learning on specific topics.As the course's lecturer, Erik Tromp has been working in big data science for almost 15 years. He has published over 20 papers academically but is best-known for his pragmatic approach to data and applying it to real-life scenarios. Because of his broad understanding of big data, data science and data architecture, Erik has been successfully teaching these concepts commercially for over a decade and received honors for his courses.For the first time ever, he has decided to make his award-winning material available to the masses digitally, providing an insanely good deal for anyone looking to learn something on data.
