This course is for students with SQL experience and now want to take the next step in gaining familiarity with distributed computing using Spark. Students will gain an understanding of when to use Spark and how Spark as an engine uniquely combines Data and AI technologies at scale. The four modules build on one another and by the end of the course the student will understand: Spark architecture, Spark DataFrame, optimizing reading/writing data, and how to build a machine learning model. The first module will introduce Spark, including how Spark works with distributed computing and what are Spark Dataframes. Module 2 covers the core concepts of Spark such as storage vs. computing, caching, partitions and Spark UI. The third module looks at Engineering Data Pipelines covering connecting to databases, schemas and type, file formats and writing good data. The final module looks at the application of Spark with Machine Learning through the business use case, a short introduction to what machine learning is, building and applying models and a final course conclusion. By understanding when to use Spark, either scaling out when the model or data is too large to process on a single machine, or having a need to simply speed up to get faster results, students will hone their SQL skills and become a more adept Data Scientist.
Este curso faz parte do Programa de cursos integrados Learn SQL Basics for Data Science
oferecido por
Programa de cursos integrados Learn SQL Basics for Data ScienceUniversidade da Califórnia, DavisInformações sobre o curso
O que você vai aprender
Use the collaborative Databricks workspace and write SQL code that executes against a cluster of machines
Use Spark UI to analyze performance and identify bottlenecks
Create an end-to-end pipeline that reads data, transforms it, and saves the result
Build a linear regression model and make predictions using SparkSQL
Habilidades que você terá
oferecido por
Universidade da Califórnia, Davis
UC Davis, one of the nation’s top-ranked research universities, is a global leader in agriculture, veterinary medicine, sustainability, environmental and biological sciences, and technology. With four colleges and six professional schools, UC Davis and its students and alumni are known for their academic excellence, meaningful public service and profound international impact.
Programa - O que você aprenderá com este curso
Introduction to Spark
In this module, you will be able to discuss the core concepts of distributed computing and be able to recognize when and where to apply them. You'll be able to identify the basic data structure of Apache Spark™, known as a DataFrame. You will be able to use the collaborative Databricks workspace and write SQL code that executes against a cluster of machines.
Spark Core Concepts
In this module, you will be able to explain the core concepts of Spark, and increase query performance by caching your data and modifying Spark configurations. You will also be able to use the Spark UI to analyze performance and identify bottlenecks.
Engineering Data Pipelines
In this module, you will be able to identify and discuss the general demands of data applications. You'll be able to access data in a variety of formats and compare and contrast the tradeoffs between these formats. You will explore and examine semi-structured JSON data, which is common in big data environments, schemas, and parallel data writes. You will be able to create an end-to-end pipeline that reads data, transforms it, and saves the result.
Machine Learning Applications of Spark
In this module, you will be able to define the basics of machine learning and identify the difference between regression and classification problems. You will build a linear regression model and use it to make predictions using Spark SQL. You will also be able to describe how machine learning fits in with concepts you learned in this course and from the other courses in this series. And lastly, you will be able to explain how a machine learning model is trained.
Avaliações
Principais avaliações do DISTRIBUTED COMPUTING WITH SPARK SQL
I highly recommend this course for anyone in the BI and Data space interested in learning Spark. The course gives an easy to understand to the framework and applicable hands on examples.
Amazing course that really cuts through the fundamentals of using distributed computing power to analyze and manipulate data. Well organised structure on fundamentals
This has been an amazing course. What is worth mentioning is how the content was delivered. Nice hands on. Highly recommended for anyone who is new to Spark
Great course, really well taught and delivered. Only thing I would say is you would really need knowledge of python to really understand this course 100%
Sobre Programa de cursos integrados Learn SQL Basics for Data Science
Perguntas Frequentes – FAQ
Quando terei acesso às palestras e às tarefas?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
- The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
- The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
O que recebo ao me inscrever nesta Especialização?
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.
Qual é a política de reembolso?
Se você se inscrever, terá 7 dias para testar sem custo e, durante este período, pode cancelar sem multa. Depois disso, não reembolsamos, mas você pode cancelar sua inscrição a qualquer momento. Veja nossa política para o reembolso total.
Existe algum auxílio financeiro disponível?
Sim, a Coursera oferece auxílio financeiro ao aluno que não possa pagar a taxa. Faça a solicitação clicando no link Auxílio Financeiro, abaixo do botão "Inscreva-se" à esquerda. Preencha uma solicitação e será notificado caso seja aprovado. Você terá que completar esta etapa para cada curso na Especialização, incluindo o Trabalho de Conclusão de Curso. Saiba mais .
Mais dúvidas? Visite o Central de Ajuda ao Aprendiz.
