【2024年】十大大數據課程熱門排行推薦與優惠精選!

 

【2024年】十大大數據課程熱門排行推薦與優惠精選!

本文章推薦「The Ultimate Hands-On Hadoop: Tame your Big Data!」、「Spark and Python for Big Data with PySpark」、「Apache Spark with Scala – Hands On with Big Data!」等相關LinkedIn線上課程,讓您滿足學習的慾望。
你是否想透過線上學習得到更多的技能,增加自己的技能樹?現在是學生的您,透過線上學習可以將更多專業知識用在課業學習上更加強所學。還是您是朝九晚五的上班族,尋找可以為工作上帶來更上一層樓的技能?或您是因為興趣或想培養其他興趣?
線上課程不受地理位置影響,不受時間早晚影響,老師來自世界各地,也不受學習程度影響的特色,讓您無時無刻想學都可以,想多看幾次增加熟悉度也可以。不同領域的老師將針對不同主題滿足您的學習目的,推薦的課程項目會陸續更新,絕對提供您最熱門人氣高的線上課程。

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目錄

  1. 大數據課程總覽
  2. 大數據課程介紹
  1. The Ultimate Hands-On Hadoop: Tame your Big Data!
  2. Spark and Python for Big Data with PySpark
  3. Apache Spark with Scala – Hands On with Big Data!
  4. Taming Big Data with Apache Spark and Python – Hands On!
  5. Big Data and Hadoop for Beginners – with Hands-on!
  6. Learn Big Data: The Hadoop Ecosystem Masterclass
  7. Taming Big Data with MapReduce and Hadoop – Hands On!
  8. Introduction to Apache NiFi | Cloudera DataFlow – HDF 2.0
  9. 大數據基礎:R 語言探索之旅
  10. Tableau高级分析: LOD表达式与TC表计算
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大數據課程總覽

為了節省您的時間,本列表整理每個課程重點資訊,讓您可以快速瀏覽這文章所提供的課程是否是您所需要的,點選您有興趣產品的「名稱」或「圖示」可以進一步跳到文章所屬的介紹區塊瞭解更多細節。

}

課程資訊
1
2
3
4
5
6
7
8
9
10
評價 4.6 分
(24,954 個評分)
4.6 分
(15,890 個評分)
4.6 分
(14,026 個評分)
4.5 分
(11,166 個評分)
4.1 分
(2,014 個評分)
4.3 分
(4,172 個評分)
4.5 分
(2,656 個評分)
4.6 分
(3,222 個評分)
4.3 分
(35 個評分)
4.8 分
(85 個評分)
學生 138,071 人人 81,867 人人 74,190 人人 63,622 人人 27,867 人人 22,839 人人 22,003 人人 13,004 人人 348 人人 330 人人
課程描述Hadoop tutorial with MapReduce, HDFS, Spark, Flink, Hive, HBase, MongoDB, Cassandra, Kafka + more! Over 25 technologies.Learn how to use Spark with Python, including Spark Streaming, Machine Learning, Spark 2.0 DataFrames and more!Apache Spark tutorial with 20+ hands-on examples of analyzing large data sets, on your desktop or on Hadoop with Scala!Apache Spark tutorial with 20+ hands-on examples of analyzing large data sets on your desktop or on Hadoop with Python!Everything you need to know about Big Data, and Learn Hadoop, HDFS, MapReduce, Hive & Pig by designing Data Pipeline.Master the Hadoop ecosystem using HDFS, MapReduce, Yarn, Pig, Hive, Kafka, HBase, Spark, Knox, Ranger, Ambari, ZookeeperLearn MapReduce fast by building over 10 real examples, using Python, MRJob, and Amazon’s Elastic MapReduce Service.Apache NiFi – An Introductory Course to Learn Installation, Basic Concepts and Efficient Streaming of Big Data Flows避開獨自摸索原文教材的高門檻,用最短時間上手R語言。——原理详解与25个案例解读

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大數據課程列表

您可以從下面資訊進一步瞭解大數據課程的價錢與最優惠的折扣、大數據課程的特色以及大數據課程介紹,發掘其他人同樣有興趣的產品還有哪些,期望您能找到滿意的!
1

The Ultimate Hands-On Hadoop: Tame your Big Data!

Hadoop tutorial with MapReduce, HDFS, Spark, Flink, Hive, HBase, MongoDB, Cassandra, Kafka + more! Over 25 technologies.

點擊前往 Udemy

課程老師Sundog Education by Frank Kane
課程評價4.6 分(24,954 個評分)
學生人數138,071 人

課程介紹

The world of Hadoop and “Big Data” can be intimidating – hundreds of different technologies with cryptic names form the Hadoop ecosystem. With this Hadoop tutorial, you’ll not only understand what those systems are and how they fit together – but you

[更多細節]

哪些人適合這堂課?

  • Software engineers and programmers who want to understand the larger Hadoop ecosystem, and use it to store, analyze, and vend “big data” at scale.
  • Project, program, or product managers who want to understand the lingo and high-level architecture of Hadoop.
  • Data analysts and database administrators who are curious about Hadoop and how it relates to their work.
  • System architects who need to understand the components available in the Hadoop ecosystem, and how they fit together.

學習目標

  • Design distributed systems that manage “big data” using Hadoop and related technologies.
  • Use HDFS and MapReduce for storing and analyzing data at scale.
  • Use Pig and Spark to create scripts to process data on a Hadoop cluster in more complex ways.
  • Analyze relational data using Hive and MySQL
  • Analyze non-relational data using HBase, Cassandra, and MongoDB
  • Query data interactively with Drill, Phoenix, and Presto
  • Choose an appropriate data storage technology for your application
  • Understand how Hadoop clusters are managed by YARN, Tez, Mesos, Zookeeper, Zeppelin, Hue, and Oozie.
  • Publish data to your Hadoop cluster using Kafka, Sqoop, and Flume
  • Consume streaming data using Spark Streaming, Flink, and Storm




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2

Spark and Python for Big Data with PySpark

Learn how to use Spark with Python, including Spark Streaming, Machine Learning, Spark 2.0 DataFrames and more!

點擊前往 Udemy

課程老師Jose Portilla
課程評價4.6 分(15,890 個評分)
學生人數81,867 人

課程介紹

Learn the latest Big Data Technology – Spark! And learn to use it with one of the most popular programming languages, Python!

One of the most valuable technology skills is the ability to analyze huge data sets, and this course is specifically design

[更多細節]

哪些人適合這堂課?

  • Someone who knows Python and would like to learn how to use it for Big Data
  • Someone who is very familiar with another programming language and needs to learn Spark

學習目標

  • Use Python and Spark together to analyze Big Data
  • Learn how to use the new Spark 2.0 DataFrame Syntax
  • Work on Consulting Projects that mimic real world situations!
  • Classify Customer Churn with Logisitic Regression
  • Use Spark with Random Forests for Classification
  • Learn how to use Spark’s Gradient Boosted Trees
  • Use Spark’s MLlib to create Powerful Machine Learning Models
  • Learn about the DataBricks Platform!
  • Get set up on Amazon Web Services EC2 for Big Data Analysis
  • Learn how to use AWS Elastic MapReduce Service!
  • Learn how to leverage the power of Linux with a Spark Environment!
  • Create a Spam filter using Spark and Natural Language Processing!
  • Use Spark Streaming to Analyze Tweets in Real Time!




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3

Apache Spark with Scala – Hands On with Big Data!

Apache Spark tutorial with 20+ hands-on examples of analyzing large data sets, on your desktop or on Hadoop with Scala!

點擊前往 Udemy

課程老師Sundog Education by Frank Kane
課程評價4.6 分(14,026 個評分)
學生人數74,190 人

課程介紹

New! Completely updated and re-recorded for Spark 3, IntelliJ, Structured Streaming, and a stronger focus on the DataSet API.

“Big data” analysis is a hot and highly valuable skill – and this course will teach you the hottest technology in big data:

[更多細節]

哪些人適合這堂課?

  • Software engineers who want to expand their skills into the world of big data processing on a cluster
  • If you have no previous programming or scripting experience, you’ll want to take an introductory programming course first.

學習目標

  • Frame big data analysis problems as Apache Spark scripts
  • Develop distributed code using the Scala programming language
  • Optimize Spark jobs through partitioning, caching, and other techniques
  • Build, deploy, and run Spark scripts on Hadoop clusters
  • Process continual streams of data with Spark Streaming
  • Transform structured data using SparkSQL, DataSets, and DataFrames
  • Traverse and analyze graph structures using GraphX
  • Analyze massive data set with Machine Learning on Spark




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4

Taming Big Data with Apache Spark and Python – Hands On!

Apache Spark tutorial with 20+ hands-on examples of analyzing large data sets on your desktop or on Hadoop with Python!

點擊前往 Udemy

課程老師Sundog Education by Frank Kane
課程評價4.5 分(11,166 個評分)
學生人數63,622 人

課程介紹

New! Updated for Spark 3, more hands-on exercises, and a stronger focus on DataFrames and Structured Streaming.

“Big data” analysis is a hot and highly valuable skill – and this course will teach you the hottest technology in big data: Apache Spark.

[更多細節]

哪些人適合這堂課?

  • People with some software development background who want to learn the hottest technology in big data analysis will want to check this out. This course focuses on Spark from a software development standpoint; we introduce some machine learning and data mining concepts along the way, but that’s not the focus. If you want to learn how to use Spark to carve up huge datasets and extract meaning from them, then this course is for you.
  • If you’ve never written a computer program or a script before, this course isn’t for you – yet. I suggest starting with a Python course first, if programming is new to you.
  • If your software development job involves, or will involve, processing large amounts of data, you need to know about Spark.
  • If you’re training for a new career in data science or big data, Spark is an important part of it.

學習目標

  • Use DataFrames and Structured Streaming in Spark 3
  • Frame big data analysis problems as Spark problems
  • Use Amazon’s Elastic MapReduce service to run your job on a cluster with Hadoop YARN
  • Install and run Apache Spark on a desktop computer or on a cluster
  • Use Spark’s Resilient Distributed Datasets to process and analyze large data sets across many CPU’s
  • Implement iterative algorithms such as breadth-first-search using Spark
  • Use the MLLib machine learning library to answer common data mining questions
  • Understand how Spark SQL lets you work with structured data
  • Understand how Spark Streaming lets your process continuous streams of data in real time
  • Tune and troubleshoot large jobs running on a cluster
  • Share information between nodes on a Spark cluster using broadcast variables and accumulators
  • Understand how the GraphX library helps with network analysis problems




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5

Big Data and Hadoop for Beginners – with Hands-on!

Everything you need to know about Big Data, and Learn Hadoop, HDFS, MapReduce, Hive & Pig by designing Data Pipeline.

點擊前往 Udemy

課程老師Andalib Ansari
課程評價4.1 分(2,014 個評分)
學生人數27,867 人

課程介紹

The main objective of this course is to help you understand the Complex Architectures of Hadoop and its components, guide you in the right direction to start with, and quickly start working with Hadoop and its components.

It covers everything tha

[更多細節]

哪些人適合這堂課?

  • This course can be opted by anyone (students, developer, manager) who is interested to learn big data. This course assumes everyone as a beginner, and teaches all fundamentals of Big Data, Hadoop and its complex architecture.

學習目標

  • Understand different technology trends, salary trends, Big Data market and different job roles in Big Data
  • Understand what Hadoop is for, and how it works
  • Understand complex architectures of Hadoop and its component
  • Hadoop installation on your machine
  • Understand how MapReduce, Hive and Pig can be used to analyze big data sets
  • High quality documents
  • Demos: Running HDFS commands, Hive queries, Pig queries
  • Sample data sets and scripts (HDFS commands, Hive sample queries, Pig sample queries, Data Pipeline sample queries)
  • Start writing your own codes in Hive and Pig to process huge volumes of data
  • Design your own data pipeline using Pig and Hive
  • Understand modern data architecture: Data Lake
  • Practice with Big Data sets




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6

Learn Big Data: The Hadoop Ecosystem Masterclass

Master the Hadoop ecosystem using HDFS, MapReduce, Yarn, Pig, Hive, Kafka, HBase, Spark, Knox, Ranger, Ambari, Zookeeper

點擊前往 Udemy

課程老師Edward Viaene
課程評價4.3 分(4,172 個評分)
學生人數22,839 人

課程介紹

Important update: Effective January 31, 2021, all Cloudera software will require a valid subscription and only be accessible via the paywall. The sandbox can still be downloaded, but the full install requires a Cloudera subscription to get access to

[更多細節]

哪些人適合這堂課?

  • This course is for anyone that wants to know how Big Data works, and what technologies are involved
  • The main focus is on the Hadoop ecosystem. We don’t cover any technologies not on the Hortonworks Data Platform Stack
  • The course compares MapR, Cloudera, and Hortonworks, but we only use the Hortonworks Data Platform (HDP) in the demos

學習目標

  • Process Big Data using batch
  • Process Big Data using realtime data
  • Be familiar with the technologies in the Hadoop Stack
  • Be able to install and configure the Hortonworks Data Platform (HDP)




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7

Taming Big Data with MapReduce and Hadoop – Hands On!

Learn MapReduce fast by building over 10 real examples, using Python, MRJob, and Amazon’s Elastic MapReduce Service.

點擊前往 Udemy

課程老師Sundog Education by Frank Kane
課程評價4.5 分(2,656 個評分)
學生人數22,003 人

課程介紹

“Big data” analysis is a hot and highly valuable skill – and this course will teach you two technologies fundamental to big data quickly: MapReduce and Hadoop. Ever wonder how Google manages to analyze the entire Internet on a continual basis? You’ll

[更多細節]

哪些人適合這堂課?

  • This course is best for students with some prior programming or scripting ability. We will treat you as a beginner when it comes to MapReduce and getting everything set up for writing MapReduce jobs with Python, MRJob, and Amazon’s Elastic MapReduce service – but we won’t spend a lot of time teaching you how to write code. The focus is on framing data analysis problems as MapReduce problems and running them either locally or on a Hadoop cluster. If you don’t know Python, you’ll need to be able to pick it up based on the examples we give. If you’re new to programming, you’ll want to learn a programming or scripting language before taking this course.

學習目標

  • Understand how MapReduce can be used to analyze big data sets
  • Write your own MapReduce jobs using Python and MRJob
  • Run MapReduce jobs on Hadoop clusters using Amazon Elastic MapReduce
  • Chain MapReduce jobs together to analyze more complex problems
  • Analyze social network data using MapReduce
  • Analyze movie ratings data using MapReduce and produce movie recommendations with it.
  • Understand other Hadoop-based technologies, including Hive, Pig, and Spark
  • Understand what Hadoop is for, and how it works




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8

Introduction to Apache NiFi | Cloudera DataFlow – HDF 2.0

Apache NiFi – An Introductory Course to Learn Installation, Basic Concepts and Efficient Streaming of Big Data Flows

點擊前往 Udemy

課程老師Stephane Maarek | AWS Certified Cloud Practitioner,Solutions Architect,Developer
課程評價4.6 分(3,222 個評分)
學生人數13,004 人

課程介紹

Apache NiFi (Cloudera DataFlows – ex Hortonworks DataFlow) is an innovative technology to build data flows and solve your streaming challenges?

In today’s big data world, fast data is becoming increasingly important. Streaming data at scale and rapi

[更多細節]

哪些人適合這堂課?

  • Beginners who want to get started on learning Apache NiFi
  • Architects who want to get an overview of Apache NiFi

學習目標

  • Install and configure Apache NiFi
  • Design Apache NiFi Architecture
  • Master core functionalities like FlowFile, FlowFile Processor, Connection, Flow Controller, Process Groups, etc.
  • Use NiFi to stream Data between different systems at scale
  • Monitor Apache NiFi
  • Integrate NiFi with Apache Kafka
  • Integration NiFi with MongoDB




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9

大數據基礎:R 語言探索之旅

避開獨自摸索原文教材的高門檻,用最短時間上手R語言。

點擊前往 Udemy

課程老師慕課 癮科技
課程評價4.3 分(35 個評分)
學生人數348 人

課程介紹

面對撲面而來的資料浪潮,包含 Google、Facebook、Intel、Pfizer、Bank of America 等國際級企業,都已經採用 R 語言進行資料分析,許多全球一流大學如 Stanford、Johns Hopkins 和 UCLA 也將 R 視為資料分析課程的先修科目。根據國際知名的 KDnuggets 論壇統計,R 語言已經連續三年獲得資料科學家最常使用的資料分析語言第一名的殊榮。

《R 語言探索之旅》以問題導向的方式教學R語言。從資料萃取和資料清理開始,有目的的進行探索性資

[更多細節]

哪些人適合這堂課?

  • 適合所有想在短時間上手 R 語言的朋友

學習目標

  • 認識 R 語言的編輯環境
  • 學會 R 語言的基本操作
  • 熟悉 R 語言的資料整理
  • 體驗 R 語言的資料分析與視覺化




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10

Tableau高级分析: LOD表达式与TC表计算

——原理详解与25个案例解读

點擊前往 Udemy

課程老師喜乐君 Wu
課程評價4.8 分(85 個評分)
學生人數330 人

課程介紹

Tableau的高级分析以LOD为代表。依赖于最受欢迎的中文LOD博客全新升级而成,从“非IT”的视角出发,建立了广义LOD的概念和体系,帮助Tableau业务分析师理解并使用高级分析表达式。

2021年全新升级内容,核心内容重新录制、重新发布,特别是关于“广义LOD表达式”的框架、四种结构性分析的典型案例、购物篮分析的高级案例等内容。同时覆盖了广受欢迎的官方15大LOD表达式内容。

•行级别函数与聚合函数的区别——理解聚合的两个层次

•行级别函数 字符串函数|日期函数|——所有的行级别表

[更多細節]

哪些人適合這堂課?

  • Tableau中高级用户
  • 大数据业务分析用户
  • 期望参加Tableau认证考试的用户

學習目標

  • 理解LOD-详细级别
  • Tableau的多种详细级别及其表达式
  • Fixed /include/exclude LOD的语法与用法
  • 15大详细级别表达式的解读
  • 表计算的逻辑和10大案例解读




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從老師查找更多大數據課程

以上推薦的大數據課程都看不到喜歡的嗎?
還是您有熱衷某個老師或某個品牌開的課程呢?嘗試從老師或品牌頁挑選吧!

【2024年】十大大數據課程熱門排行推薦與優惠精選!

參考其他資料科學線上課程

除了本文介紹的課程種類以外,想要瞭解資料科學領域還有哪些不同類型的課程值得一探究竟嗎?讓您可以從不同面向更紮實的學習,點擊參考以下其他熱門主題文章。絕對提供您最優惠人氣滿檔的課程,歡迎繼續延伸閱讀。


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