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专业数据工程师 在 Python 中
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专业数据工程师 在 Python 中
先决条件
数据工程师Course
Discover modern data architecture's key components, from ingestion and serving to governance and orchestration.
Course
Unix 命令行帮助用户以新方式组合现有程序、自动化重复任务,并在集群和云上运行程序。
Course
掌握虚拟机、容器、Docker 和 Kubernetes 的基础知识。 了解差异,快速上手!
Course
本课程介绍 dbt,用于数据建模、转换、测试和构建文档。
Course
掌握面向对象编程(OOP)的基础概念,构建自定义类和对象!
Course
Conquer NoSQL and supercharge data workflows. Learn Snowflake to work with big data, Postgres JSON for handling document data, and Redis for key-value data.
Course
In this Introduction to DevOps, you’ll master the DevOps basics and learn the key concepts, tools, and techniques to improve productivity.
Course
Master Python testing: Learn methods, create checks, and ensure error-free code with pytest and unittest.
Project
Sharpen your debugging skills to enhance sales data accuracy.
Course
了解 Docker 入门,掌握它在数据专业人士工具箱中的重要性。 了解 Docker 容器、镜像等内容。
Course
精通 PySpark,轻松处理大数据——学习处理、查询和优化海量数据集,释放强大分析能力!
Chapter
This chapter introduces the exciting world of Big Data, as well as the various concepts and different frameworks for processing Big Data. You will understand why Apache Spark is considered the best framework for BigData.
Chapter
The main abstraction Spark provides is a resilient distributed dataset (RDD), which is the fundamental and backbone data type of this engine. This chapter introduces RDDs and shows how RDDs can be created and executed using RDD Transformations and Actions.
Chapter
In this chapter, you'll learn about Spark SQL which is a Spark module for structured data processing. It provides a programming abstraction called DataFrames and can also act as a distributed SQL query engine. This chapter shows how Spark SQL allows you to use DataFrames in Python.
Project
Step into a data engineer's shoes and master data cleaning with PySpark on an e-commerce orders dataset!
Chapter
In this chapter, we learn how to download data files from web servers via the command line. In the process, we also learn about documentation manuals, option flags, and multi-file processing.
Chapter
In the last chapter, we bridge the connection between command line and other data science languages and learn how they can work together. Using Python as a case study, we learn to execute Python on the command line, to install dependencies using the package manager pip, and to build an entire model pipeline using the command line.
Course
Learn about the difference between batching and streaming, scaling streaming systems, and real-world applications.
Course
Master Apache Kafka! From core concepts to advanced architecture, learn to create, manage, and troubleshoot Kafka for real-world data streaming challenges!
Course
In this course, you will learn the fundamentals of Kubernetes and deploy and orchestrate containers using Manifests and kubectl instructions.
Resource
Understand how data engineering can impact your business.
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