Shulou(Shulou.com)06/03 Report--

Brief introduction of big data

Big data (big data), IT industry term, refers to the data set that can not be captured, managed and processed with conventional software tools within a certain period of time. It is a massive, high growth rate and diversified information asset that requires a new processing model to have stronger decision-making power, insight and process optimization ability.

Brief introduction of artificial Intelligence

Artificial intelligence (Artificial Intelligence), abbreviated as AI. It is a new technical science that studies and develops theories, methods, technologies and application systems used to simulate, extend and expand human intelligence. Artificial intelligence is a branch of computer science, which attempts to understand the essence of intelligence and produce a new intelligent machine that can respond in a similar way to human intelligence. research in this field includes robots, language recognition, image recognition, natural language processing and expert systems. Since the birth of artificial intelligence, the theory and technology have become increasingly mature, and the field of application has been constantly expanding. It can be imagined that the scientific and technological products brought by artificial intelligence in the future will be the "containers" of human wisdom. Artificial intelligence can simulate the information process of human consciousness and thinking. Artificial intelligence is not human intelligence, but it can think like human and may surpass human intelligence.

(1) is the motivation for transformation based on the high wages in this industry?

Generally speaking, people who want to change careers see a high salary level and a high demand for talent in this industry. But on the other hand, the industry also requires high comprehensive ability of talents. It doesn't just require you to know some technical details. At the same time, you also need to understand some business logic.

Relatively speaking, a transition to this industry is not recommended over the age of 30. As the saying goes, there is a certain truth in "changing careers to poverty for three years". Moreover, this industry is an emerging industry and the market responds quickly. Basically, it will be implemented after the product manager converts the business requirements into development requirements on the same day, so 996 is standard on a daily basis.

Therefore, when considering high salary, we should also consider high input and high output. Only when the two are unified can they be worthy of the salary paid by the company.

(2) can the transformation be achieved through 3-6 months of training?

1, look at the money, see how much money you have in your pocket, and then see how much the training costs, and work out the unit price of each day's input.

2, look at employment salary, the core of training is to get you employed, while the rest are slogans. Look at the average salary of trainees who have been trained in the past and how long they have been in the new unit.

3, look at the situation of the teachers, look at the teachers' big data project experience and project situation.

(3) is there still a shortage of people in big data's industry? what are the employment prospects?

1. Any industry is according to the law of 20% and 80%. Big data's industry is now very short of the top 20% of compound talents.

2, as a professional big data cross-pedestrian look back, training can enable you to find a job, but better development depends on yourself.

3, a simple standard of judgment, look at the money! Look at the median salary, look at the median training fee, and then weigh your self-discipline with time before signing up for training (or consult me first, WeChat: 383116569).

(4) what is the employment trend of human beings under the coverage of artificial intelligence in the future?

Simply, the work of repetitive classes will be largely replaced. Then there will be a large number of jobs that require experience and a sense of service. There will be a phenomenon of machines repairing machines in the future, but how to manage and maintain these machines will create a large number of jobs. Just like the current ride-hailing drivers and takeout boys. New technologies will drive new requirements, and if you don't improve your skills, thinking, and horizons, you may be eliminated by the times.

(5) will big data's employment be a "brick farmer"?

Most of them are not, but you should learn to constantly upgrade and add equipment at any time.

Big data employment is a very broad concept, mainly divided into technology and business direction.

(1) to put it simply, the direction of technology can be divided into primary, medium and high. It mainly revolves around technical implementation.

The beginners are some data acquisition, tagging, SQL statements, Python. This kind of work.

Intermediate is generally based on these will be some modular development, can better achieve a function, to complete the more advanced functions of the data.

The senior level belongs to the architecture or director level, the technical details should not only be understood, but also optimize the code and implementation patterns from the perspective of architecture. To be able to translate business requirements into R & D needs.

(2) the business direction is also simple at the beginning, medium and high levels. It mainly revolves around business transformation.

The primary level is mainly to understand the business, familiar with the product, may involve user research, product design. But it won't be too deep.

Intermediate mainly in-depth understanding of the business, through some methods and statistical knowledge to find the needs of users, to meet the needs of users in the process.

Advanced business is mainly operational relationships, bidding, solution capabilities, be able to know the boundary between technology and business, know the implementation process and details of the project.

Big data's employment should not go through just one point and think that he has seen a face, which contains a lot of content. First master the technology and then learn and develop other abilities little by little.

(6) how should I plan if I want to work in big data in finance?

1. To establish a correct understanding, big data and artificial intelligence are only a technical means. The business understanding of finance is what you need to know and understand when you are in college.

2. I have always thought that university is a general education. For technologies such as big data and AI, you only need to know how to use them and match the relevant financial scenarios. It is not too late to implement specific technologies at work. Moreover, these technological changes are also changing with each passing day. In college, the general contents of mathematics, graph theory, probability theory, financial derivatives, macro and microeconomics are suggested to read more and understand more.

3. Set up the concept of "Tao" and "skill" in everything. At the best age in college, you should make more efforts on "Tao". At the level of "skill", training institutions and self-study communities will also help you do it.

(7) the future direction of big data's major in colleges and universities? Should you work first or go to graduate school first?

It is recommended that you first look for a job, and then work while studying as a graduate student, focusing on algorithm-related problems or AI-related problems encountered in your work. There are three reasons:

1, the economic aspect: vulgar, that is, money. After all, the undergraduate course to find a 8K~1W about big data marking engineer should be no problem.

2, Vision: only in your work will you know what you have learned in college is useless and what is useful. When there is only work experience, and then through the theoretical knowledge of graduate students to in-depth understanding of your work, will be of great help to your future career development.

3, career development: now big data's development is more and more close to the business, so the demand for people's comprehensive ability is getting higher and higher. Only the big data talents of the code are bound to be replaced by the new forces, and optimize their own mode of thinking more. Close to the business, help others more, read more, learn more!

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