At present, the big data industry is extremely popular. Many people are full of interest in big data. The salary offered in the market is also very attractive. There are many students with zero basic knowledge who have not learned programming languages, and even rarely have access to computers. That is to say 0 Basic can't learn big data? the answer is negative.
100 people have 100 Hamlets in their hearts. Learning big data is not easy, but it is not inscrutable. Through hard work, friends with zero basic knowledge can also master big data technology. 0Basic learning big data is mainly divided into the following four modules:
The learning of computer programming languages
For zero-based friends, first of all, you need to master a computer programming language. Everyone knows that there are many computer programming languages, such as: R, C++, JAVA and so on. Java is one of the most widely used network programming languages. It is easy to learn and easy to use. When learning the Java part of big data training , we generally need to learn these courses: HTML&CSS&JS, java foundation, JDBC and database, JSP java web technology, jQuery and AJAX technology, SpringMVC, Mybatis, Hibernate etc.
2. Understand the theory of big data
To learn big data, you should at least know what big data is and what fields big data is generally used in. Have a general understanding of big data foundation, such as Linux system management, Shell programming, Maven deployment/configuration/warehouse, Maven POM, etc.
3. Learning about big data related courses
After learning a programming language, you can generally take part of the big data course . Many training institutions on the market have less learning of big data courses than Java. Please pay attention to such institutions. We are learning big data, not Java. And our Jami Valley big data course is much longer than the learning time of Java, including HDFS distributed file system, MapReduce distributed computing model, Yarn distributed resource manager, Zookeeper distributed coordination service, Hbase distributed database, Hive distributed Data warehouse, FlumeNG distributed data acquisition system + Sqoop big data migration system, Scala big data golden language + kafka distributed bus system, SparkCore big data computing cornerstone + SparkSQL data mining tool + SparkStreaming streaming computing platform, SparkMllib machine learning platform + SparkGraphx graph computing platform, etc. These courses are essential if you want to learn big data completely.
Fourth, the actual combat of big data projects
The actual project is equally important. The operation and practice of the actual project can help us better understand the content we have learned, and at the same time can strengthen the memory of the relevant knowledge. As a professional big data training institution, Gamigu Big Data, during the students' study period, is equally important. There will be practical projects such as e-commerce data offline analysis platform, mobile base station signal monitoring big data, operation and maintenance big data platform, and public opinion big data platform for students to choose and train.