How many math courses do you need to take for AI?

Here I am: Advanced Mathematics (preferably Mathematical Analysis), Linear Algebra (Preferably Advanced Algebra), Probability Theory, Statistics, Graph Theory, the above is just a primer. Then there is matrix theory, convex optimization (which is essential for in-depth research), and the rest is stochastic processes, information theory (depending on the direction of personal research).

For real variable functions, complex variable functions, and functional analysis, if you are very theoretical, you can go to self-study to see. If machine learning, data mining, pattern recognition are all math lessons, then even more.

From elementary school, advanced mathematics, functions, about 6 seven mathematics, however, there are many mathematics-related courses, and these courses will be used in the process of learning, and then practiced.

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In the case of artificial intelligence, I think it is necessary to learn a lot of math courses, for example, at the very least, to learn advanced mathematics.

In addition to basic mathematics, computer science, and programming languages, there are also behavioral sciences, statistics, brain science, sociology, philosophy, linguistics, automatic control, and so on.

AI needs to learn all math lessons, but AI learns fast and can solve problems by typing knowledge.

There are a lot of courses to be learned in the Institute of Artificial Intelligence, and he should learn most of the courses in human culture.

Artificial intelligence still learns a lot of courses. You can study, for example, the integration of mathematics and the rationalization.

I still take a lot of courses. You can study, for example, the integration of mathematics and the rationalization.

High math is enough, python is learned in a day, and then with the help of open source models, face recognition, face swapping, target tracking, and so on are no problem.

Advanced Mathematics, Linear Algebra, Probability Theory and Mathematical Statistics, Discrete Mathematics This is just a mathematics course, in addition to mathematics, you will also learn all the professional courses in computer science and technology and electronic circuits at the undergraduate level.

In essence, artificial intelligence cannot constitute an independent discipline, at most it is an interdisciplinary discipline, and the main direction of attack includes three major aspects: learning, recognition and reasoning, which has high requirements for mathematics, and there are many courses, which may not be enough for undergraduates.

I studied artificial intelligence (the new AI class of Xi'an Jiaotong this year).

At present, we have to learn high mathematics, line algebra, probability theory, and complex transformation, and it seems that there are many more.

Just one physics, biomimetic science!

Integral transformations, such as the Fourier transform, the Laplace transform, and wavelet analysis.

I think if I give me 100 million a year, I can't learn artificial intelligence, I can't do it just like mathematics, not to mention that this is the beginning, it's really good, 666

Similar to the basic courses of the Department of Mathematics, the principles of comparative AI are mathematical.

High Mathematics, Linear Algebra, Probability Theory.

Learn mathematics, physics and chemistry well, and you will not be afraid to go all over the world.

The courses studied in the AI major include professional foundation courses and professional core courses.

Professional courses: Professional basic courses: Introduction to Artificial Intelligence Application, Programming Basics, Python Application Development, Linux Operating System, Database Technology, Computer Network Technology, Artificial Intelligence Mathematics Basics.

Professional core courses: artificial intelligence data service, computer vision application development, deep learning application development, natural language processing application development, intelligent speech processing and application development, artificial intelligence system deployment and operation and maintenance, artificial intelligence comprehensive project development.

Introduction: Artificial intelligence is a comprehensive discipline that includes computer, cybernetics, information theory, neurophysiology, psychology, linguistics and other disciplines. Artificial intelligence is the study of how to create artificial intelligent machines or intelligent systems from the perspective of computer application systems to simulate the ability of human intelligent grasping and energy activities, as well as the extension of human intelligence science.

Employment direction of artificial intelligence major:

1. Scientific research institutions.

Artificial intelligence is an emerging interdisciplinary discipline, integrating various disciplines such as computer, psychology, and philosophy, and the research field is broad and deep, which can be robots, sensors, intelligent devices, etc. With the wide application of this field, the demand for scientific research on artificial intelligence is also huge, and various scientific research institutions are one of the best places for artificial intelligence professionals.

2. Software and hardware development.

With the continuous development of artificial intelligence, it will change the way of writing, updating, and releasing the first one, and the development and operation will also be more automated, and the programming assistant based on artificial intelligence, automated testing and compilation, and simplified error fixing can all be applied to the software development segment. Hardware development is also a prerequisite for the realization of artificial intelligence, and the growing demand for AI hardware also brings more employment opportunities.

3. AI-related computer language development.

Artificial intelligence is now popular all over the world, in order to do a good job in artificial intelligence, AI development is a necessary skill, and computer language development is an important way to realize AI application, so the importance of related language development is self-evident.

4. Lecturer in universities and training institutions.

The popularity of artificial intelligence remains high, major universities have opened artificial intelligence majors, and the demand for professional teachers is also rising year by year.

The main courses studied in the university are "Artificial Intelligence, Society and Humanities", "Artificial Intelligence or Town Bureau Philosophical Foundations and Ethics", "Advanced Robot Control", "Cognitive Robots", "Robot Planning and Learning", "Bionic Robots", "Swarm Intelligence and Autonomous Systems", "Unmanned Technology and System Implementation", "Game Design and Development", "Computer Graphics", "Virtual Reality and Augmented Reality", "Modern Methods of Artificial Intelligence I", "Problem Expression and Solution" , "Modern Methods of Artificial Intelligence II", "Machine Learning, Natural Language Processing, Computer Vision", etc.

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Artificial intelligence needs to learn the basic courses.

a.First you need a foundation in mathematics: Advanced Mathematics, Linear Algebra, Probability Theory, Mathematical Statistics and Stochastic Processes, Discrete Mathematics, Numerical Analysis.

b.secondly, the accumulation of algorithms is needed: artificial neural networks, support vector machines, genetic algorithms and other algorithms; Of course, there are algorithms needed in various fields, for example, if you want to let the robot navigate the location environment and build a travel map by itself, you need to study SLAM; In short, there are many algorithms, which take time to accumulate;

c.Then, you need to master at least one programming language, after all, the implementation of the algorithm still needs to be programmed; If you go deep into hardware, some basic electrical courses are essential.

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