数据工程师、数据科学家和数据分析师项目掌握课程 (英文)

Pyspark 为数据工程师和数据分析师提供的 1H30 教程

发布时间：2024年5月
视频格式：MP4 | 视频：h264, 1920×1080 | 音频：AAC, 44.1 KHz
语言：英语 | 文件大小：718.86 MB | 时长：1小时41分钟

2024年数据工程师、数据科学家和数据分析师的端到端项目，精通 PySpark

你将学到什么：
无需任何先决条件即可掌握扎实的 PySpark 技能
避免初学者常见错误并掌握最佳实践
通过 PySpark 考试、认证和技术测试
课程结束时将获得培训证书
具备竞争工作机会所需的 PySpark 技能
深入了解关键的 PySpark 概念
使用 PySpark 实现专业项目
作为自由职业者使用 PySpark 工作
获得在使用 PySpark 的公司工作所需的技能
掌握成为数据工程师、数据科学家或数据分析师必需的 PySpark 核心概念

需求：
本课程从 A 到 Z 全面覆盖，无需任何先决条件。

描述：
精通 PySpark 成为数据工程师、数据科学家或数据分析师
本课程旨在通过 Python 上的 PySpark 框架培训您，该框架被数据工程师、数据科学家和数据分析师广泛用于处理大量数据。

获取 PySpark 的基本技能
不再需要在 Google 上搜索信息；您的学习精髓集中在此课程中。

快速学习以有效地发展技能
本课程设计使您能够快速有效地熟悉 PySpark。仅通过几个小时和两个项目，您将掌握脱颖而出所需的知识。

最新课程，定期更新
本课程更新于 2024 年，与目前公司在 PySpark 方面的技能需求保持一致。

避免初学者的陷阱
本课程突出了经验丰富的 PySpark 开发者的最佳实践，帮助您编写专业质量的源源代码。

在您的考试、技术测试和 PySpark 认证中获得成功
本课程内容结构旨在有效准备您应对大学考试、认证和与 PySpark 相关的技术测试。

在公司中获得职位或从事自由职业任务
PySpark 是企业和自由职业环境中最受追捧的框架之一。接受这个库的培训为您开启了众多职业机会的大门。
Pyspark For Data Engineers And Data Analysts In 1H30Pyspark For Data Engineers And Data Analysts In 1H30

Published 5/2024
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 718.86 MB | Duration: 1h 41m

Mastering PySpark with an End-to-End Project for Data Engineers, Data Scientists and Data Analysts in 2024

What you’ll learn
Gain solid PySpark skills with no prerequisites
Avoid beginner pitfalls and master best practices
Pass PySpark exams, certifications and technical tests
Receive a training certificate at the end of the course
Have the necessary PySpark skills to compete for job opportunities
Gain a solid understanding of key PySpark concepts
Realize professional projects with PySpark
Work as a freelance with PySpark.
Acquire the skills needed to work with companies that use PySpark
Master the essential concepts in PySpark to become a Data Engineer, Data Scientist or Data Analyst

Requirements
This course covers everything from A to Z. There are no prerequisites.

Description
Mastering PySpark to Become a Data Engineer, Data Scientist, or Data AnalystThis course aims to train you in the PySpark framework on Python, which is widely used by Data Engineers, Data Scientists, and Data Analysts to handle large volumes of data.Acquire Fundamental Skills in PySparkNo more hunting for information on Google; the essence of your learning is concentrated in this course.Learn Quickly for Effective Skill DevelopmentThis course is designed to familiarize you with PySpark quickly and effectively. In just a few hours and through two projects, you will possess the necessary knowledge to stand out.Recent Course, Regularly UpdatedUpdated in 2024, this training is in line with the skills currently sought after in PySpark by companies.Avoid Beginner’s TrapsThe course highlights the best practices of an experienced PySpark developer to help you produce professional-quality code.Succeed in Your Exams, Technical Tests, and PySpark CertificationsThe course content is structured to effectively prepare you for your university exams, certifications, and technical tests related to PySpark.Secure a Position in a Company or Undertake Freelance AssignmentsPySpark is among the most coveted frameworks in both corporate and freelance settings. Training in this library opens the door to numerous professional opportunities.Train for In-Demand CareersIn 2024, the demand for Data Scientists, Data Engineers, Data Analysts, and other Big Data-related professions is on the rise. Now is the perfect time to train for these professions by learning to master PySpark.Work for Top CompaniesRenowned companies such as Uber, Netflix, Airbnb, Amazon, Meta (formerly Facebook), and Microsoft, are currently seeking skilled professionals in PySpark.Obtain a Completion CertificateA certificate confirming that you have followed and completed the course will be awarded at the end of the training.

Overview
Section 1: Get Started With PySpark for Data Engineers, Data Scientists, and Data Analysts

Lecture 1 Let’s Get Started With PySpark!

Section 2: Project Setup

Lecture 2 How to Use Google Colab or Kaggle to Make the Project

Section 3: Complete Big Data Project Using PySpark

Lecture 3 Project Overview

Lecture 4 Data Source

Lecture 5 Install PySpark on Google Colab and Create a Spark Session

Lecture 6 Import Data Into a Spark DataFrame

Lecture 7 Store Data Files on Google Drive

Lecture 8 Rename and Delete Columns in a Data Table

Lecture 9 Create and Add New Columns in a Spark DataFrame

Lecture 10 Before Continuing the Course…

Lecture 11 Filter a PySpark Dataframe with Conditions

Lecture 12 Group Data and Create New Columns Based on Existing Data

Lecture 13 Join PySpark Dataframes

Lecture 14 Perform Operations With Columns and Delete Unnecessary Data

Lecture 15 Create Statistical Columns

Lecture 16 Use Window Functions

Lecture 17 Create The Final Spark Data Table

Lecture 18 End of The PySpark Project

Section 4: Download The Complete Python Code For The PySpark Project

Lecture 19 Download The Code

Section 5: End of The PySpark Course

Lecture 20 Conclusion and Tips For Your Career

People with little or no programming experience who want to learn PySpark,People who want to develop expertise with PySpark,People who want to apply for jobs or freelance positions that require PySpark skills

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