Informações sobre o curso
4.7
3 classificações
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!...
Globe

cursos 100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Calendar

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Advanced Level

Nível avançado

Clock

Approx. 6 hours to complete

Sugerido: 4 weeks of study, 6-8 hours/week...
Comment Dots

English

Legendas: English...
Globe

cursos 100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Calendar

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Advanced Level

Nível avançado

Clock

Approx. 6 hours to complete

Sugerido: 4 weeks of study, 6-8 hours/week...
Comment Dots

English

Legendas: English...

Programa - O que você aprenderá com este curso

Week
1
Clock
4 horas para concluir

Basics of real-time data processing

...
Reading
9 vídeos (Total de 48 min), 5 leituras, 5 testes
Video9 videos
Delivery semantics6min
Approaches to real-time data processing7min
Data storages for real-time big data processing6min
Introduction to Kafka5min
Kafka pros and cons3min
Kafka CLI6min
How to submit your first assignment3min
How to Install Docker on Windows 7, 8, 104min
Reading5 leituras
Assignments. General requirements10min
Slack Channel is the quickest way to get answers to your questions10min
Docker Installation Guide10min
FAQ How to show your code to teaching staff10min
Grading System: Instructions and Common Problems10min
Quiz3 exercícios práticos
Introduction to the world of big data real-time processing. Delivery semantics12min
Data storages for real-time big data processing. Kafka16min
Basics of real-time data processing18min
Week
2
Clock
3 horas para concluir

Spark Streaming

...
Reading
3 testes
Week
3
Clock
2 horas para concluir

NoSQL. Cassandra

...
Reading
13 vídeos (Total de 68 min), 3 testes
Video13 videos
CAP theorem5min
Cassandra Architecture4min
Read-Write Path6min
Cassandra Data Model5min
Virtual nodes2min
Gossip Protocol5min
Building Applications with Cassandra3min
Getting Started with CQL7min
Accessing Cassandra from Python7min
Static Columns4min
Overcoming Cassandra's Limitation3min
Secondary Indexes4min
Quiz3 exercícios práticos
Basics of NoSQL18min
Apache Cassandra16min
NoSQL. Cassandra14min
Week
4
Clock
2 horas para concluir

NoSQL. Redis

...
Reading
7 vídeos (Total de 46 min), 2 testes
Video7 videos
Command line interface8min
Python interface6min
Strings, Lists, Hashes5min
Sets, Sorted Sets, HyperLogLogs6min
Transactions6min
Advanced features6min
Quiz1 exercício prático
Redismin

Instrutores

Alexey A. Dral

Founder and Chief Executive Officer
BigData Team

Sobre 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....

Sobre o Programa de cursos integrados Big Data for Data Engineers

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

Perguntas Frequentes – FAQ

  • Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.

  • Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.

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