We all know that big data is very popular nowadays, and many small partners are also consulting with Mr. Rong about how to learn big data, such as: how to learn big data?
For the introduction of big data learning, the basis is different, the starting point will be different. Today, let’s first say that for the zero-based students want to learn the way and method of big data! Many people may feel incredible, how can zero-based learn big data, how can we get started without programming basis? In fact, this view is very good.Correctly, for the development of big data, it needs a certain programming basis, so our big data entry-level course falls into the study of programming language.
Now the general training institute’s big data introductory course is taught from programming language, but you must recognize that programming language is only a small part of the big data course. If a large part of the whole big data course is taught by programming language, you should be careful. This is really not true.Big data course. There are also some “goblin” institutions that confuse the standard course of real big data teaching with the knowledge of HTML5, Java, big data visualization, and so on, so as to deceive the students and regret when they find it. We summarize the following vacation lessons to avoid students entering the pit.
The unreliable training courses on big data are summarized as follows:
1、Big data HTML5
The course focuses on HTML5, css, HTMl, AJAX, jQuery, AngleJs, Js and other contents.
2、Big data Java
The course focuses on Java, Java Web, Spring, Spring MVC, MyBatis, HTCargo project practice.
3、Visualization of Big Data on the Big Size
4、Big Data Bias Test Course
The course focuses on database management system (DBMS), VBScript scripting language and so on.
Reliable training courses on big data are as follows:
In this course, students should master computer technology, hadoop, spark, storm development, hive database, Linux operating system, distributed storage, distributed computing framework and other technologies, and be familiar with large data processing and analysis technology.
Among them, the function and development technology of each module in the big data ecosystem, including HDFS in Hadoop system, Hbase for data operation, MapReduce for data development, YARN for resource allocation, Hive for data warehouse, PIg carries out data analysis, as well as Oozie, Zookeeper, Sqoop and Flume modules. There is also Spark ecosystem learning, its Scala foundation and SpakSQL development.