Shulou(Shulou.com)06/03 Report--

A large number of new technologies emerge in big data field every year, which become an effective means for big data to obtain, store, process analysis or visualization. Big data technology can mine the information and knowledge hidden in large-scale data, provide a basis for human social and economic activities, improve the operational efficiency in various fields, and even the intensive degree of the whole social economy. It is precisely because of the advantages shown by big data's technology that more and more people choose to enter the big data industry, so how to learn big data's technology? What do you have to learn?

Here I still want to recommend the big data Learning Exchange Group I built myself: 529867072, all of them are developed by big data. If you are studying big data, the editor welcomes you to join us. Everyone is a software development party. Irregularly share practical information (only related to big data software development), including the latest big data advanced materials and advanced development tutorials sorted out by myself. Welcome to join us if you want to go deep into big data.

Big data course is roughly divided into eight stages. The following is an overview of the course. You can refer to it for specific reference.

The first stage, the foundation of Java language

Java development introduction, familiar with Eclipse development tools, Java language foundation, Java flow control, Java strings, Java arrays and classes and objects, digital processing classes and core technologies, Imando O and reflection, multithreading, Swing programs and collection classes.

The second stage, HTML, CSS and Java

PC website layout, HTML5+CSS3 foundation, WebApp page layout, native Java interactive function development, Ajax asynchronous interaction, jQuery application.

Phase III, JavaWeb and database

Database, JavaWeb development core, JavaWeb development insider.

The fourth stage, Linux&Hadoopt system

Linux system, Hadoop offline computing outline, distributed database Hbase, data warehouse Hive, data migration tools Sqoop, Flu.

The fifth stage, actual combat (real project of first-line company)

Data acquisition, data processing, data analysis, data presentation, data application.

The sixth stage, Spark ecosystem

Python programming language, Scala programming language, Spark big data processing, Spark-Streaming big data processing, Spark-Mlib machine learning, Spark-GraphX

Figure calculation, actual combat one: recommendation system based on Spark (real project of a front-line company), actual combat two: Sina (http://www.sina.com.cn)).

The seventh stage, Storm ecosystem

Storm technical architecture, Storm principles and fundamentals, message queuing kafka, Redis tools, zookeeper detailed explanation, practice 1: log alarm system project, practice 2: guess you like to recommend the system.

The eighth stage, big data Analysis-AI (artificial Intelligence)

Data Analyze work environment preparation & basic data analysis, data visualization, Python machine learning:

1. Python machine learning

2. Image recognition & neural network, natural language processing & social network processing, actual combat project: outdoor equipment recognition analysis.

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