Where do I start with big data?

The demand for jobs in big data or cloud computing will increase and become a very popular career on the internet. How do I start with big data?

The Big Data course teaches with real commercial data sources that are dedicated to the energy integration and blockchain of big data systems as a supplement Practical project: Big data distribution is based on the Spark1.6 storage framework, that keeps up with the times. Spark2x, Spark lessons increase by 3 weeks so students get the incredible big data development technology from a single source.

The course requires a total of six months of focused training and is divided into five learning phases:



Here I would like to recommend the big data learning exchange group that I set up: 199427210, the group is learning all big data development. If you are learning big data the editors greet you, everyone is an infrequent software development party Share dry goods (related to big data software development only) including a copy of the latest advanced big data materials and advanced tutorials that I organized myself. Welcome advanced and small partners who want to dig deeper into big data to become a member.

The first phase is the foundation of the Java language. This stage is the initial stage of big data, mainly for learning some concepts, characters, process control, etc. of the Java language

Phase two is the Linux Foundation and the Hadoop ecosystem. In this phase we mainly master the flexible use of the Linux operating system. Master one of the core technologies of the big data Hadoop ecosystem.

Phase three is distributed computing. Mainly master the use of the Scala language and various data structures, and explain in detail a number of core concepts of the spark such as structure, installation, operation, theoretical concepts, etc. There is also Storm real-time development. Storm is mainly used to solve real-time computer problems.

The fourth phase is mainly cases of actual combat projects. During this time all knowledge should be integrated and practical skills developed quickly through actual struggles to ensure a certain work ability.

The fifth level is the technical knowledge related to big data analysis, mainly to explain the basics of data analysis. Data analysis, data visualization and there are three types of naive bayes algorithms in sklearn and so on!

There are many modules for big data development and learning, and they are active in many directions too. They are a multidirectional development and not restricted by the industry.