Big Data for Data Engineers Specialization

开始时间: 10/20/2018 持续时间: Unknown

所在平台: Coursera专项课程

课程类别: 计算机科学

大学或机构: CourseraNew



Explore 1600+ online courses from top universities. Join Coursera today to learn data science, programming, business strategy, and more.


第一个写评论        关注课程


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.


5 courses

Big Data Essentials: HDFS, MapReduce and Spark RDD

Have you ever heard about such technologies as HDFS, MapReduce, Spark? Always wanted to learn these new tools but missed concise starting material? Don’t miss this course either! In this 6-week course you will: - learn some basic technologies of th

Big Data Analysis: Hive, Spark SQL, DataFrames and GraphFrames

No doubt working with huge data volumes is hard, but to move a mountain, you have to deal with a lot of small stones. But why strain yourself? Using Mapreduce and Spark you tackle the issue partially, thus leaving some space for high-level tool

Big Data Applications: Machine Learning at Scale

Machine learning is transforming the world around us. To become successful, you’d better know what kinds of problems can be solved with machine learning, and how they can be solved. Don’t know where to start? The answer is one button away. During thi

Big Data Applications: Real-Time Streaming
Starts October 2018
There is a significant number of tasks when we need not just to process an enormous volume of data but to process it as quickly as possible. Delays in tsunami prediction can cost people’s lives. Delays in traffic jam prediction cost extra time. Advertisements based on the recent users’ activity are ten times more popular. However, stream processing techniques alone are not enough to create a complete real-time system. For example to create a recommendation system we need to have a storage that allows to store and fetch data for a user with minimal latency. These databases should be able to store hundreds of terabytes of data, handle billions of requests per day and have a 100% uptime. NoSQL databases are commonly used to solve this challenging problem. After you finish this course, you will master stream processing systems and NoSQL databases. You will also learn how to use such popular and powerful systems as Kafka, Cassandra and Redis. To get the most out of this course, you need to know Hadoop and Hive. You should also have a working knowledge of Spark, Spark SQL and Python. Do you want to learn how to build Big Data applications that can withstand modern challenges? Jump right in!

Big Data Services: Capstone Project
Starts December 2018
Are you ready to close the loop on your Big Data skills? Do you want to apply all your knowledge you got from the previous courses in practice? Finally, in the Capstone project, you will integrate all the knowledge acquired earlier to build a real application leveraging the power of Big Data. You will be given a task to combine data from different sources of different types (static distributed dataset, streaming data, SQL or NoSQL storage). Combined, this data will be used to build a predictive model for a financial market (as an example). First, you design a system from scratch and share it with your peers to get valuable feedback. Second, you can make it public, so get ready to receive the feedback from your service users. Real-world experience without any 3G-glasses or mock interviews.


Deep Learning Specialization on Coursera


俄罗斯搜索巨头Yandex推出的面向数据工程师的大数据专项课程系列(Big Data for Data Engineers Specialization) ,这个系列包括4门子课程和1门毕业项目课程,涵盖HDFS,MapReduce, Spark, Hive, Spark SQL, 大规模机器学习,实时流处理等,感兴趣的同学可以关注: Build Your Data Engineering Skills-Learn how to tame the big data beast with the most popular tools assisted by top-notch practitioners


大数据 大数据课程 大数据专项课程 数据工程师 数据工程师课程 数据科学 Yandex HDFS MapReduce Spark Hive 大规模机器学习 spark_sql 实时流处理