课程信息
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第 4 门课程(共 5 门)

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

高级

完成时间大约为18 小时

建议:4 weeks of study, 4-8 hours/week...

英语(English)

字幕:英语(English)

您将获得的技能

KafkaNoSQLSpark StreamingSpark

第 4 门课程(共 5 门)

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

高级

完成时间大约为18 小时

建议:4 weeks of study, 4-8 hours/week...

英语(English)

字幕:英语(English)

教学大纲 - 您将从这门课程中学到什么

1
完成时间为 16 分钟

Welcome to the course "Big Data Applications: Real-Time Streaming"

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4 个视频 (总计 6 分钟), 1 个阅读材料
4 个视频
Real-Time Streaming Course Structure2分钟
Meet Artyom56
Meet Ivan1分钟
1 个阅读材料
Slack Channel is the quickest way to get answers to your questions10分钟
完成时间为 7 小时

Basics of real-time data processing

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12 个视频 (总计 57 分钟), 4 个阅读材料, 5 个测验
12 个视频
Real-time processing of Big Data4分钟
Delivery semantics6分钟
Approaches to real-time data processing5分钟
Lambda and Kappa Architectures6分钟
Introduction1分钟
Data storages for real-time big data processing6分钟
Introduction to Kafka6分钟
Kafka pros and cons4分钟
Kafka CLI7分钟
How to submit your first assignment3分钟
How to Install Docker on Windows 7, 8, 104分钟
4 个阅读材料
Assignments. General requirements10分钟
Docker Installation Guide10分钟
FAQ How to show your code to teaching staff10分钟
Grading System: Instructions and Common Problems10分钟
3 个练习
Introduction to the world of big data real-time processing. Delivery semantics12分钟
Data storages for real-time big data processing. Kafka16分钟
Basics of real-time data processing18分钟
2
完成时间为 5 小时

Spark Streaming

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6 个视频 (总计 34 分钟), 1 个阅读材料, 5 个测验
6 个视频
Spark Streaming concept6分钟
How to write Spark Streaming application6分钟
Spark Streaming hints6分钟
Spark Streaming and delivery semantics8分钟
Exactly once extended4分钟
1 个阅读材料
Spark streaming tasks. General guidelines10分钟
2 个练习
Spark Streaming12分钟
Spark Streaming: final18分钟
3
完成时间为 2 小时

NoSQL. Cassandra

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13 个视频 (总计 68 分钟), 3 个测验
13 个视频
CAP Theorem5分钟
Cassandra Architecture4分钟
Read-Write Path6分钟
Cassandra Data Model5分钟
Virtual Nodes2分钟
Gossip Protocol5分钟
Building Applications with Cassandra3分钟
Getting Started with CQL7分钟
Accessing Cassandra from Python7分钟
Static Columns4分钟
Overcoming Cassandra's Limitation3分钟
Secondary Indexes4分钟
3 个练习
Basics of NoSQL18分钟
Apache Cassandra16分钟
NoSQL. Cassandra14分钟
4
完成时间为 3 小时

NoSQL. Redis

...
7 个视频 (总计 50 分钟), 2 个测验
7 个视频
Command line interface8分钟
Python interface7分钟
Strings, Lists, Hashes5分钟
Sets, Sorted Sets, HyperLogLogs7分钟
Transactions7分钟
Advanced features7分钟
1 个练习
Redis12分钟

讲师

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Alexey A. Dral

Founder and Chief Executive Officer
BigData Team
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Artyom Vybornov

Team Lead at Rambler&Co
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Vladislav Goncharenko

DCAM MIPT, Skoltech
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Ivan Mushketyk

Software Engineer, ConsenSys

关于 Yandex

Yandex is a technology company that builds intelligent products and services powered by machine learning. Our goal is to help consumers and businesses better navigate the online and offline world....

关于 Big Data for Data Engineers 专项课程

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. 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....
Big Data for Data Engineers

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