Phase 1: Java language fundamentals

1, Java language fundamentals

Introduction to Java development, familiar with the Eclipse development tools, Java language fundamentals, Java flow control, Java strings, Java arrays and classes and objects, digital Processing classes and core technologies, I/O and reflection, multi-threading, Swing programs and collection classes.

2, HTML, CSS and JavaScript

PC website layout, HTML5+CSS3 basics, WebApp page layout, native JavaScript interactive function development, Ajax asynchronous interaction, jQuery applications.

3, JavaWeb and Database

Database, JavaWeb development core, JavaWeb development insider.

Phase 2: Linux& Hadoop ecosystem

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

Phase 3: Distributed Computing Framework

1, Distributed Computing Framework

Python programming language, Scala programming language, Spark big data processing, Spark-Streaming big data processing, Spark-Mlib Machine Learning, Spark-GraphX Graph Computation, and two projects with hands-on content.

2, storm technology architecture system

Storm principles and fundamentals, message queue kafka, Redis tools, zookeeper details, two hands-on content.

Phase 4: big data project practice

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

Phase 5: Big Data Analyze

1, Data Analyze work environment preparation & data analysis basics, data visualization, Python machine learning;

2, image recognition & neural networks, natural language processing & social network processing, 1 project combat.

Through the above understanding of Java + big data learning route, we can see that when learning big data technology, students need to master a certain Java language foundation, which also means that if you are a Java technology beginner want to go back to learn big data technology, is also a good choice.