|
所在平台: Coursera专项课程 课程类别: 计算机科学 大学或机构: CourseraNew |
课程主页: https://www.coursera.org/specializations/big-data-engineering
课程评论：没有评论
课程名称：大数据数据工程师专业化 概述：该专业课程专为处理数据（无论是小数据还是大数据）的人士设计。如果您是数据分析师、数据科学家、数据工程师或数据架构师（或希望成为其中之一），不容错过扩大您在大数据工程和大规模数据分析领域的知识和技能的机会。 在四个简明的课程中，您将学习Hadoop、MapReduce、Spark的基础知识，离线数据处理方法用于数据仓库、实时数据处理和大规模机器学习。此外，您还将参与一个顶点项目，以构建和部署自己的大数据服务，使您的作品集更加具有竞争力。 在专业课程的学习过程中，您将完成渐进加难的编程作业（主要使用Python）。确保您具备一定的Python经验。该课程将提高您为常见的大数据任务设计解决方案的技能，包括： - 创建批处理和实时数据处理管道， - 进行大规模机器学习， - 将机器学习模型部署到生产环境中——以及更多内容！ 加入一些优秀的大数据实操专家，向他们学习基础知识和行业技巧。 特别感谢教授Mikhail Roytberg（MIPT APT系）、Oleg Sukhoroslov（中国科学院院士，IITP RAS高级研究员）、Oleg Ivchenko（MIPT APT系）、Pavel Akhtyamov（MIPT APT系）、Vladimir Kuznetsov、Asya Roitberg、Eugene Baulin和Marina Sudarikova。 课程大纲： 1. 大数据基础：HDFS、MapReduce和Spark RDD 2. 大数据分析：Hive、Spark SQL、DataFrames和GraphFrames 3. 大数据应用：大规模机器学习 4. 大数据应用：实时流处理
Big Data Essentials: HDFS, MapReduce and Spark RDD
Big Data Analysis: Hive, Spark SQL, DataFrames and GraphFrames
Big Data Applications: Machine Learning at Scale
Big Data Applications: Real-Time Streaming
This specialization is made for people working with data (either small or big). If you are a Data Analyst, Data Scientist, Data Engineer or Data Architect (or you want to become one) — don’t miss the opportunity to expand your knowledge and skills in the field of data engineering and data analysis on the large scale. In four concise courses you will learn the basics of Hadoop, MapReduce, Spark, methods of offline data processing for warehousing, real-time data processing and large-scale machine learning. And Capstone project for you to build and deploy your own Big Data Service (make your portfolio even more competitive). Over the course of the specialization, you will complete progressively harder programming assignments (mostly in Python). Make sure, you have some experience in it. This course will master your skills in designing solutions for common Big Data tasks: - creating batch and real-time data processing pipelines, - doing machine learning at scale, - deploying machine learning models into a production environment — and much more! Join some of best hands-on big data professionals, who know, their job inside-out, to learn the basics, as well as some tricks of the trade, from them. Special thanks to Prof. Mikhail Roytberg (APT dept., MIPT), Oleg Sukhoroslov (PhD, Senior Researcher, IITP RAS), Oleg Ivchenko (APT dept., MIPT), Pavel Akhtyamov (APT dept., MIPT), Vladimir Kuznetsov, Asya Roitberg, Eugene Baulin, Marina Sudarikova.
