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所在平台: Udemy |
课程主页: https://www.udemy.com/course/real-world-data-science-with-spark-2/
课程评论：没有评论
课程名称：用Spark进行现实数据科学 课程概述：您是否希望扩展在Spark中执行数据科学操作的知识？无论您是一位希望了解Spark中算法实现的数据科学家，还是一位具有最少开发经验的新手，想要学习大数据分析，这门课程都非常适合您。Spark是处理大数据的理想解决方案，因其与Hadoop相比更简单的开发过程而受到数据分析师和工程师的广泛欢迎。这是一个高效的大规模数据处理引擎，课程旨在帮助您自信地进行实时数据处理。 课程内容：本课程经过精心设计，旨在赋予您关于Spark的相关信息。课程涵盖Spark 2的基础知识、核心数据处理框架和API、安装以及应用开发设置。从真实案例介绍Spark编程模型，学习如何使用Spark流处理Twitter数据，包括数据收集、清洗和可视化。接下来，您将熟悉Spark中的机器学习算法及不同的机器学习技巧，并学习在数据集上应用统计分析和挖掘操作。此外，课程将探讨图处理分析，并通过一个端到端的案例研究整合您所学的内容。完成课程后，您将能够将所学知识运用于更快速、更高效的大数据项目中。 为什么选择这门课程？Packt课程经过精心设计，致力于提供最佳的学习体验。课程结合了文本、视频、代码示例和测验，使学习过程充满趣味和收获。我们通过广泛的研究和策划准备了本课程，每个部分都朝着掌握Spark的方向逐步展开，以模块化的方式呈现。 讲师介绍：本课程汇聚了几位声誉卓著的讲师，包括Eric Charles（数据科学领域有10年经验，Datalayer创始人）、Bikramaditya Singhal（具有7年行业经验的数据科学家，专注于统计分析和机器学习）以及Srinivas Duvvuri（Broadridge Financial Solutions的高级副总裁，负责大数据和数据科学中心）。此外，Rajanarayanan Thottuvaikkatumana拥有超过23年的软件开发经验，涉及多个技术领域。 通过本课程，您将深入了解如何利用Spark进行数据科学操作，提升您的数据分析技能。
Are you looking forward to expand your knowledge of performing data science operations in Spark? Or are you a data scientist who wants to understand how algorithms are implemented in Spark, or a newbie with minimal development experience and want to learn about Big Data analytics? If yes, then this course is ideal you. Let's get on this data science journey together. When people want a way to process Big Data at speed, Spark is invariably the solution. With its ease of development (in comparison to the relative complexity of Hadoop), it's unsurprising that it's becoming popular with data analysts and engineers everywhere. It is one of the most widely-used large-scale data processing engines and runs extremely fast. The aim of the course is to make you comfortable and confident at performing real-time data processing using Spark. What is included? This course is meticulously designed and developed in order to empower you with all the right and relevant information on Spark. However, I want to highlight that the road ahead may be bumpy on occasions, and some topics may be more challenging than others, but I hope that you will embrace this opportunity and focus on the reward. Remember that throughout this course, we will add many powerful techniques to your arsenal that will help us solve the problems. Let's take a look at the learning journey. The course begins with the basics of Spark 2 and covers the core data processing framework and API, installation, and application development setup. Then, you'll be introduced to the Spark programming model through real-world examples. Next, you'll learn how to collect, clean, and visualize the data coming from Twitter with Spark streaming. Then, you will get acquainted with Spark machine learning algorithms and different machine learning techniques. You will also learn to apply statistical analysis and mining operations on your dataset. The course will give you ideas on how to perform analysis including graph processing. Finally, we will take up an end-to-end case study and apply all that we have learned so far. By the end of the course, you should be able to put your learnings into practice for faster, slicker Big Data projects. Why should I choose this course? Packt courses are very carefully designed to make sure that they're delivering the best learning experience possible. This course is a blend of text, videos, code examples, and quizzes, which together makes your learning journey all the more exciting and truly rewarding. This helps you learn a range of topics at your own speed and also move towards your goal of learning the technology. We have prepared this course using extensive research and curation skills. Each section adds to the skills learned and helps you to achieve mastery of Spark. This course is an amalgamation of sections that form a sequential flow of concepts covering a focused learning path presented in a modular manner. We have combined the best of the following Packt products: Data Science with Spark by Eric CharlesSpark for Data Science by Bikramaditya Singhal and Srinivas DuvvuriApache Spark 2 for Beginners by Rajanarayanan Thottuvaikkatumana Meet your expert instructors: For this course, we have combined the best works of these extremely esteemed authors: Eric Charles has 10 years of experience in the field of data science and is the founder of Datalayer, a social network for data scientists. He is passionate about using software and mathematics to help companies get insights from data. Bikramaditya Singhal is a data scientist with about 7 years of industry experience. He is an expert in statistical analysis, predictive analytics, machine learning, Bitcoin, Blockchain, and programming in C, R, and Python. He has extensive experience in building scalable data analytics solutions in many industry sectors. Srinivas Duvvuri is currently the senior vice president development, heading the development teams for fixed income suite of products at Broadridge Financial Solutions (India) Pvt Ltd. In addition, he also leads the Big Data and Data Science COE and is the principal member of the Broadridge India Technology Council. Rajanarayanan Thottuvaikkatumana, Raj, is a seasoned technologist with more than 23 years of software development experience at various multinational companies. He has worked on various technologies including major databases, application development platforms, web technologies, and Big Data technologies.
