Shulou(Shulou.com)06/02 Report--

With the development of big data in China, big data-related talents are in short supply, and big data analyst is called "one of the professions with good prospects for future development" by the media. Big data analysts are paid 20 per cent more than their peers. And how to become a trend rider in the big data era, mastering the current shortage of software skills is the key, then, zero foundation how to learn big data?

Big data, as a very popular IT technology, the number of friends who want to learn from big data has changed from one to two, from two to three, but the number of counting units is also from one to a hundred to ten thousand, and then it may be even higher. Is big data's study easy? The threshold is low, anyone who wants to learn can start big data's study, so how to get started?

one

What is big data?

In fact, to put it simply, big data assists decision-making by analyzing and mining full amount of non-sampling data.

The applications that big data can achieve can be summarized in two directions, one is precision customization, and the second is prediction. For example, like searching for the same content through a search engine, everyone's results are very different. For example, precision marketing, Baidu promotion, Taobao like recommendation, or you go to a place, automatically recommend to you the surrounding consumer facilities and so on.

Here I still want to recommend the big data Learning Exchange Group I built myself: 251956502, all of them are developed by big data. If you are studying big data, the editor welcomes you to join us. Everyone is a software development party. Irregularly share practical information (only related to big data software development), including the latest big data advanced materials and advanced development tutorials sorted out by myself. Welcome to join us if you want to go deep into big data.

two

Is it easy for big data to learn zero basics?

With the rapid development of big data's industry, some problems have also emerged. for example, the lack of talents in big data is a problem that needs to be solved urgently at present. well, many people who learn from big data have some problems again. that is, what everyone is generally worried about is whether zero foundation can learn from big data, will it be difficult to learn?

Do people with zero foundation want to go to large number training institutions to learn big data development? The answer is yes. Go. Big data's study is not unfathomable, although it is not so simple for zero-foundation students, but as long as you study hard, coupled with the guidance of professional teachers and targeted training, I believe you can also fully master big data.

three

Big data's four steps in Zero fundamentals

Students with zero foundation should not be in a hurry to learn from big data's development. they should be completed step by step step by step, which can be divided into four steps:

The first stage: understand the basic concepts of big data

First of all, when learning a course, you should have a simple understanding of the course. for example, you should first learn some professional terms of the course, learn some basic concepts and know what the course is all about. what are the main learning knowledge? Then to learn big data, you must know what big data is. In general, what are big data's fields of application, so as to avoid learning blindly when you know nothing about big data.

The second stage: learning computer programming language

For friends with zero foundation, getting started may not be so easy. You need to learn a lot of theoretical knowledge and read boring textbooks. Because it is very difficult to master a computer programming language. We all know that there are a lot of computer programming languages, such as: RMagol CentralPhonePythonMagol Java and so on.

The third stage: big data's related study courses

After the first two stages of basic learning, we have basically mastered the programming language, and then we can learn some of big data's courses. Here, the editor would like to remind everyone: the real big data in the industry, 82% of the lectures are hadoop, spark ecosystem, storm real-time development, beginners must recognize whether what you want to learn is the real big data!

The fourth stage: the actual combat phase of the project

Practical training can help us to better understand what we have learned and at the same time enhance our memory of relevant knowledge. In the future practical application, we can get started faster, and we also have experience in the use of relevant knowledge.

Nothing in the world is difficult for those who set their minds to it, no matter whether you have a foundation or no foundation, as long as you seriously study big data, you will certainly learn well.

Finally: follow-up improvement

Big data combined with artificial intelligence can be a real data scientist.

Machine learning: is a multi-domain cross-discipline, involving probability theory, statistics, approximation theory, convex analysis, algorithm complexity theory and other disciplines. It is the core of artificial intelligence and the fundamental way to make computers intelligent. It is widely used in all fields of artificial intelligence. It mainly uses induction, synthesis rather than deduction. The machine learning algorithm is basically fixed, and it is relatively easy to learn.

Deep learning: the concept of deep learning originates from the research of artificial neural network and has developed rapidly in recent years. Examples of deep learning applications include AlphaGo, face recognition, image detection and so on. It is a scarce talent at home and abroad, but deep learning is relatively difficult, and the algorithm is updated relatively fast, so we need to learn from experienced teachers.

The fastest way to learn is to learn from industry experts. after all, teachers have accumulated experience for many years, and they can get twice the result with half the effort by taking fewer detours.

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