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Is big data good for self-study or for training institutions?
It is best to go to a training institution. What big data needs to learn is very complicated and difficult to learn. Choosing to teach yourself big data, many problems are beyond your ability to solve. There are many problems that you can't solve in your study that will pop up from time to time, which will affect your confidence in learning big data.

1, the professionalism of teachers.

Choosing a good teacher will make your learning process much easier and smoother. Seeing a teacher depends on whether the teacher has experience. An experienced teacher will make you take fewer detours. It will be much easier to communicate with the teacher when encountering problems.

2. The way of class.

Big data is a technology that needs to be practiced very much. It is best to choose offline teaching methods, especially for friends who have no foundation or weak foundation, or have poor self-control ability. When choosing a big data training institution, it must be noted that offline training can shorten your learning cycle and ensure your learning efficiency.

3. Is there any project training?

Because big data is a technology that requires a lot of practice and operation, when choosing a training institution, you should check whether there are any projects that can be practiced. In the end, we still have to face employment. If you want to find a good job, projects are very important.

4. Learning environment and atmosphere.

It's time for everyone to enjoy a good learning environment. If you have a good choice, why not choose a training company with a comfortable environment and a good learning atmosphere?

Learning big data Note:

1. First, learn big data. First, understand what big data is and its general application. Learning technology is not an easy task at first, and it requires enough determination and perseverance.

2. For zero-based friends, you need to master a computer programming language. There are many computer programming languages, and Java is one of the most widely used network programming languages at present.