Graduate students What courses do you study in artificial intelligence

Pattern recognition and intelligent control.

Artificial intelligence is a new technical science that studies and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence. Artificial intelligence is a branch of computer science that attempts to understand the essence of intelligence and produce a new kind of intelligent machine that can respond in a similar way to human intelligence, including robotics, 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 application field has been expanding.

Artificial intelligence is a simulation of the information process of human consciousness and thinking. Artificial intelligence is not human intelligence, but it can think like a human being, and may surpass human intelligence.

It mainly depends on the direction you choose as a graduate student. There are many directions for artificial intelligence, and it depends on what aspects of your school are offered. Such as: only robots, CAD systems, CAI systems, etc.!

The development status of artificial intelligence is in the growth period, and due to the relatively small number of related talents, the talent market for artificial intelligence is vacant, and there is a situation where supply exceeds demand. In addition, the state has issued relevant policies to promote the development of artificial intelligence; Some provinces are also paying more attention to the development of artificial intelligence.

Artificial intelligence, requires a foundation in mathematics: advanced mathematics, linear algebra, probability theory, mathematical statistics and stochastic processes, discrete mathematics, numerical analysis.

The accumulation of algorithms is required: artificial neural networks, support vector machines, genetic algorithms, etc.; Of course, there are algorithms needed in various fields, such as SLAM needs to be studied to allow robots to navigate and map the location environment by themselves; In short, there are many algorithms, which take time to accumulate.

It is necessary to master at least one programming language: after all, the implementation of algorithms still needs to be programmed; If you go deep into hardware, some basic electrical courses are essential.

The main majors of artificial intelligence are "Artificial Intelligence, Society and Humanities", "Philosophical Foundations and Ethics of Artificial Intelligence", "Advanced Robot Control", "Cognitive Robots", "Robot Planning and Learning", and "Bionic Robots".

"Swarm Intelligence and Autonomous Systems", "Unmanned Driving 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" and other courses.

The training direction of artificial intelligence major.

1) Research related directions of basic theories of artificial intelligence, such as: artificial intelligence models and theories, mathematical foundations of artificial intelligence, learning methods of optimization theory, machine learning theory, brain science and brain-like intelligence, etc.

3) Research directions of artificial intelligence supporting technologies, such as artificial intelligence architecture and systems, artificial intelligence development tools, artificial intelligence frameworks and intelligent chips, etc.

4) Research directions related to artificial intelligence application technology, including but not limited to: intelligent manufacturing, robotics, unmanned driving, intelligent networked vehicles, intelligent transportation, intelligent medical care, machine translation and scientific computing, etc., give full play to the enabling role of artificial intelligence in various disciplines or fields, and form a characteristic training direction.

5) Research directions related to artificial intelligence and intelligent social governance, such as artificial intelligence ethics and governance based on the close integration of artificial intelligence technical attributes and social attributes, as well as related technical directions in terms of trusted security, fairness, and privacy protection.

The above content refers to Encyclopedia - Artificial Intelligence.

1. Research direction.

The main research directions of the Master of Artificial Intelligence include:

Advanced Artificial Intelligence, Machine Learning & Knowledge Discovery, Pattern Recognition, Intelligent Systems, Image Measurement Technology, Robotics, Computer Vision, Cognitive Neuroscience, Bioinformatics, Biostatistics, and Systems Biology.

In addition to the above directions, its combination with communications, network security, etc., can lead to many other application directions, including:

1. Electronics and Communication Engineering: Fundamentals of Information Network Protocols, Fundamentals of Data Network Theory, Coding Theory, Digital Signal Processing, (ii) Wisdom Drafting, Digital Image Analysis, Signal Detection and Estimation, Computational Electromagnetics, Advanced Electromagnetic Field Theory, Microwave Network Theory and Applications.

2. Computer technology: advanced computer architecture, parallel algorithms, advanced computer networks, advanced operating systems, advanced software engineering, advanced database systems, advanced artificial intelligence, modern cryptography theory and practice, machine learning and knowledge discovery, deep learning, reinforcement learning, algorithm design and analysis.

In addition, there are many interdisciplinary research directions such as network and information security, big data technology and engineering, smart logistics, energy and smart management of the environment.

2. Training program.

Graduate students majoring in artificial intelligence can study both full-time and part-time. The basic length of study for full-time study is 2 to 3 years; The basic study period of part-time study should be appropriately extended. The maximum length of study is normally five years.

At the same time, most of its master's education implements a dual-tutor system. One of the tutors is from the school (i.e. the on-campus tutor), who is a teacher with a high academic level and rich experience in mentoring, mainly supervising students' course studies and degrees**; Another supervisor is required to come from the practice unit of the graduate student (i.e., the practice supervisor), who is an expert with rich experience in engineering practice, and mainly guides the learning of the student's professional practice.

Influenced by the characteristics of the major, professional practice is an important part of graduate students to gain practical experience and improve their practical ability. Therefore, graduate students in this major direction should carry out professional practice, which can be combined with centralized practice and segmented practice. Professional practice should have clear task requirements and assessment indicators, and the practical results can reflect the achievements of such master's degree students in terms of artificial intelligence research ability and discipline literacy.

In general, the practical time should not be less than 6 months, and the professional practice time of graduate students without work experience should not be less than 1 year.

The main courses studied in the artificial intelligence major are: society and humanities, philosophical foundations and ethics of artificial intelligence, and advanced robot control.

Cognitive Robotics, Robot Planning and Learning, Bionic Registry Robots, Swarm Intelligence and Autonomous Systems, Unmanned Driving Technology and System Implementation, Game Design and Development, Computer Graphics, Virtual Reality and Augmented Reality

Modern Methods of Artificial Intelligence I, Problem Expression and Solving, Modern Methods of Artificial Intelligence II, Machine Learning, Natural Language Processing, Computer Vision.

Learning coarse grinding artificial intelligence requires learning cognitive psychology, neuroscience fundamentals, human memory and learning, language and thinking, computational neural engineering, and other related professional knowledge.

1. Cognitive and neuroscience course groups.

Specific courses: Cognitive Psychology, Fundamentals of Neuroscience, Human Memory and Learning, Language and Thinking, Computational Neural Engineering.

2. Artificial Intelligence Ethics Course Group.

Specific courses: "Artificial Intelligence, Society and Humanities", "Philosophical Foundations and Ethics of Artificial Intelligence".

3. Science and engineering course group.

The development of a new generation of artificial intelligence requires the joint efforts of experimental scientists and theoretical scientists in brain science, neuroscience, cognitive psychology, information science and other related disciplines to find breakthroughs in artificial intelligence.

4. Advanced robotics course group.

Specific courses: "Advanced Robot Control", "Cognitive Robot", "Robot Planning and Learning", "Bionic Robot".

5. Artificial intelligence platform and tool course group.

Specific courses: "Swarm Intelligence and Autonomous Systems", "Unmanned Driving Technology and System Implementation", "Game Design and Development", "Computer Graphics", "Virtual Reality and Augmented Reality" ......

6. Artificial intelligence core course group.

Specific courses: "Modern Methods of Artificial Intelligence I", "Problem Expression and Solving", "Modern Methods of Artificial Intelligence II", "Machine Learning, Natural Language Processing, Computer Vision, etc".