Apache Projects Big Data Fundamental

Qualified for CPFA® Big Data Fundamental for Apache Projects (CF)

Duration: 1 Day

Overview

An adequate understanding of open source software, the pro-and-con of open source software adoption, Apache projects landscape with selected widely-adopted signature Apache big data and AI projects.

For private classes, please contact us at (852) 2116 3328 for more details.

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Course Objectives

Designed for anyone who wants to have good understanding about the world's leading eco-system of open source software managed by Apache.

Learn and understand the open sourced, battle-tested, and enterprise production ready Big Data and AI software, and gain a better understanding of strategies of adopting the advanced open source data technologies.

Intended Audience

Anyone who are interested in the world of Apache open-source technology and the development in Big Data field.

Course Outline

Through introductions of a mix of the latest methodologies and technologies utilised by the world’s large organizations, attendees will learn how to choose Apache software projects to gain competitive advantages.

  • Why open source leads Big Data and AI technologies
  • 7Vs of Big Data and the Apache’s solutions for 7Vs
  • Structured and Unstructured Data
  • Introduction of Apache Hadoop - De Facto Standard of Big Data
  • Introduction of Apache HBase - De Facto Standard of Big Data NoSQL
  • Introduction of Apache Spark - De Facto Standard of Machine Learning
  • Introduction of Apache Kafka - Fast Data for Big Data
  • Introduction of tools and mythologies on Big Data Analytics

Trainer

Mr. Patrick Tsoi

  • Certified Professional for Apache projects Trainer
  • Doctor of Education (in progress), Hong Kong Baptist University
  • Master in IT in Education, University of Hong Kong
  • Bachelor of Engineering in System Engineering and Engineering Management, Chinese University of Hong Kong
  • Over 20+ years in the IT training field, and work includes complex projects applying data science, and software development in Finance, Data Science and Quantitative Analysis

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