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Which direction is better for my postgraduate entrance examination for artificial intelligence?
1, pure theory, with strong artificial intelligence or neural network as the research direction. Undergraduate students can choose neuroscience, psychology, philosophy and computer science.

2. From the optimization of artificial intelligence at the algorithmic level, it is natural for undergraduates to study computer science, but they also need to take some small subjects that attach importance to logic or self-study, such as game theory.

3. Industrial application. You should mainly study automation and mechanical control.

First, the artificial intelligence professional employment prospects:

The prospects are good. China is undergoing industrial upgrading, and industrial robots and artificial intelligence will be strong hotspots, which will happen in three to five years. The difficulty is definitely high, which requires you to have innovative thinking ability. Calculus and series in advanced mathematics must be good, software programming (basic and most widely used language: C/C++) must be good, microelectronics (digital circuits, low-frequency and high-frequency analog circuits, and most importantly, embedded programming ability) must be well studied, and you must also have certain mechanical design ability (spatial thinking ability is very important). In this case, you are the talent, and you are the talent in the field of artificial intelligence that China urgently needs in the next five years. If you delve deeply into a subject, you will become an expert or even a master in this field.

Second, the artificial intelligence professional employment direction:

Artificial intelligence can be said to be a sophisticated discipline, which belongs to the intersection of social science and natural science, involving mathematics, psychology, neurophysiology, information theory, computer science, philosophy and cognitive science, uncertainty theory and cybernetics. Research fields include natural language processing, machine learning, neural network, pattern recognition, intelligent search and so on. Applications include machine translation, language and image understanding, automatic programming, expert system and so on.

If you focus on academic and theoretical research, then the major recommends "applied mathematics". At present, machine learning Machine learning is essentially an application scenario in the fields of differential equations, probability theory and matrix analysis. Deep learning, which has flourished in recent years, is a branch of machine learning that is very close to artificial intelligence.

Do not rule out the current automation, communication, machinery.

To a certain extent, other majors will also move closer to intelligence. No matter what major, you can learn relevant knowledge after class, especially in this era of high-quality learning resources at your fingertips and lifelong learning. However, in the overall curriculum arrangement, this major will still be different from other majors, and one advantage of this is that there will be some extra points when taking the postgraduate entrance examination. The disadvantage is that if you don't take the postgraduate exam, the average employment situation will be weaker than other majors. After all, the social recognition of this major is not high, and it is undergraduate.