課程信息
17,749 次近期查看

Learner Career Outcomes

100% 在線

立即開始,按照自己的計劃學習。

第 4 門課程(共 5 門)

可靈活調整截止日期

根據您的日程表重置截止日期。

高級

完成時間大約為23 小時

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

英語(English)

字幕:英語(English)

您將獲得的技能

KafkaNoSQLSpark StreamingSpark

Learner Career Outcomes

100% 在線

立即開始,按照自己的計劃學習。

第 4 門課程(共 5 門)

可靈活調整截止日期

根據您的日程表重置截止日期。

高級

完成時間大約為23 小時

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

英語(English)

字幕:英語(English)

教學大綱 - 您將從這門課程中學到什麼

1
完成時間為 16 分鐘

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

4 個視頻 (總計 6 分鐘), 1 個閱讀材料
4 個視頻
Real-Time Streaming Course Structure2分鐘
Meet Artyom56
Meet Ivan1分鐘
1 個閱讀材料
Slack Channel is the quickest way to get answers to your questions10分鐘
完成時間為 7 小時

Basics of real-time data processing

12 個視頻 (總計 57 分鐘), 4 個閱讀材料, 5 個測驗
12 個視頻
Real-time processing of Big Data4分鐘
Delivery semantics6分鐘
Approaches to real-time data processing5分鐘
Lambda and Kappa Architectures6分鐘
Introduction1分鐘
Data storages for real-time big data processing6分鐘
Introduction to Kafka6分鐘
Kafka pros and cons4分鐘
Kafka CLI7分鐘
How to submit your first assignment3分鐘
How to Install Docker on Windows 7, 8, 104分鐘
4 個閱讀材料
Assignments. General requirements10分鐘
Docker Installation Guide10分鐘
FAQ How to show your code to teaching staff10分鐘
Grading System: Instructions and Common Problems10分鐘
3 個練習
Introduction to the world of big data real-time processing. Delivery semantics12分鐘
Data storages for real-time big data processing. Kafka16分鐘
Basics of real-time data processing18分鐘
2
完成時間為 5 小時

Spark Streaming

6 個視頻 (總計 34 分鐘), 1 個閱讀材料, 5 個測驗
6 個視頻
Spark Streaming concept6分鐘
How to write Spark Streaming application6分鐘
Spark Streaming hints6分鐘
Spark Streaming and delivery semantics8分鐘
Exactly once extended4分鐘
1 個閱讀材料
Spark streaming tasks. General guidelines10分鐘
2 個練習
Spark Streaming12分鐘
Spark Streaming: final18分鐘
3
完成時間為 2 小時

NoSQL. Cassandra

13 個視頻 (總計 69 分鐘), 3 個測驗
13 個視頻
CAP Theorem5分鐘
Cassandra Architecture4分鐘
Read-Write Path6分鐘
Cassandra Data Model5分鐘
Virtual Nodes2分鐘
Gossip Protocol5分鐘
Building Applications with Cassandra4分鐘
Getting Started with CQL7分鐘
Accessing Cassandra from Python7分鐘
Static Columns4分鐘
Overcoming Cassandra's Limitation3分鐘
Secondary Indexes4分鐘
3 個練習
Basics of NoSQL18分鐘
Apache Cassandra16分鐘
NoSQL. Cassandra14分鐘
4
完成時間為 3 小時

NoSQL. Redis

7 個視頻 (總計 50 分鐘), 2 個測驗
7 個視頻
Command line interface8分鐘
Python interface7分鐘
Strings, Lists, Hashes5分鐘
Sets, Sorted Sets, HyperLogLogs7分鐘
Transactions7分鐘
Advanced features7分鐘
1 個練習
Redis12分鐘

講師

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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

關於 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....

關於 Big Data for Data Engineers 專項課程

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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