Artificial Intelligence Professional Examination subjects include the foundation of mathematics, computer fundamentals, machine learning and data mining, deep learning and artificial intelligence algorithms, natural language processing and knowledge mapping.
I. Mathematical Foundations
Mathematical Foundations is a very important subject in the Artificial Intelligence Professional Examination. It includes advanced mathematics, linear algebra, probability theory and mathematical statistics. These mathematical fundamentals are the basis for conducting research and application of artificial intelligence algorithms, and are important for understanding and analyzing various artificial intelligence algorithms.
Second, computer fundamentals
Computer fundamentals is an essential subject in the examination of artificial intelligence. It includes computer networks, operating systems, database principles and applications, and so on. These basic courses can help students understand the basic operating principles of computer systems, master programming skills and data processing methods, laying the foundation for the subsequent design and implementation of artificial intelligence algorithms.
Three, machine learning and data mining
Machine learning and data mining is one of the core subjects in the examination of artificial intelligence. Machine learning studies how computer algorithms enable computer systems to have the ability to learn on their own, and data mining aids decision-making by extracting useful information from large amounts of data. Mastering this knowledge is very important for conducting research and application of artificial intelligence algorithms.
Four, deep learning and artificial intelligence algorithms
Deep learning is one of the cutting-edge technologies in the field of artificial intelligence, which imitates the structure and working principle of the neural network of the human brain, and realizes the analysis and processing of complex patterns through multi-level feature learning and abstract representation. Mastering deep learning algorithms and their applications is of great significance for graduate students majoring in artificial intelligence.
V. Natural Language Processing and Knowledge Graph
Natural Language Processing is one of the important research directions in the field of Artificial Intelligence, which researches how to enable computers to understand and process human natural language. Knowledge graph, on the other hand, integrates a large amount of structured knowledge and relationships into a single graph that provides support for machine understanding and reasoning. Mastering the technology related to natural language processing and knowledge graph is of great significance to the graduate students majoring in artificial intelligence.
Six, Computer Vision and Pattern Recognition
Computer vision and pattern recognition is another important research direction in the field of artificial intelligence, research on how to achieve the understanding and analysis of images and videos by computer. Mastering techniques related to computer vision and pattern recognition is very important for performing tasks such as image processing and target recognition.
VII, Intelligent Systems and Applications
Intelligent Systems and Applications is a comprehensive subject for the Artificial Intelligence Major Examination, which involves the application of AI algorithms in various fields. Studying Intelligent Systems and Applications enables exam students to understand the specific application scenarios of artificial intelligence in the fields of healthcare, finance, transportation, etc., and to be able to design and implement corresponding intelligent systems.