Neusoft Education relies on Neusoft's profound technological accumulation and industry application capabilities in the artificial intelligence industry, closely integrates industrial resources and educational resources, formulates talent training plans, determines professional positioning, training goals and curriculum settings, and uses joint teaching and joint teaching between schools and enterprises. By building laboratories, internship training bases, we realize the complementary advantages of educational resources and industrial resources, and cultivate high-quality talents with theoretical knowledge and skills related to artificial intelligence to meet society's demand for talents.

The collaborative education system for cultivating AI professionals at Donghua University focuses on integrating industry and education, aiming to train engineering talents who are proficient in mathematics, natural sciences, computer science, data science, and artificial intelligence. Students are required to have practical engineering skills, communication and collaboration abilities, computational thinking, and data thinking. They should be able to work in the field of artificial intelligence and related industries, such as developing intelligent systems, and possess lifelong learning abilities and innovative spirit.

In-depth mastery of computer science knowledge and artificial intelligence technology and practical applications

• Master solid computer science knowledge, including systems, data structures, algorithms, OS, databases, compilation, etc., and be good at C++/Java/Python programming.
• Solid foundation in mathematics and statistics. Master mathematical and statistical knowledge such as linear algebra, probability theory, statistics, and calculus.
• In-depth understanding of the basic theories, algorithms and models of machine learning and deep learning. Master core theories and technologies such as digital image processing, intelligent speech processing, computer vision, and natural language processing.
• Accurately meet enterprise needs, be familiar with tools and frameworks such as PaddlePaddle, TensorFlow, Keras or PyTorch, and understand their usage methods and principles.

Innovative engineering capabilities that integrate software development and artificial intelligence must have the mathematical foundation of software development and artificial intelligence, master AI core technologies and mainstream tools, have teamwork and innovative spirit, and be able to engage in intelligent software design, development, testing, etc.

Curriculum system constructs
A school-enterprise co-construction OBE curriculum system, establishes talent training goals and requirements, and designs a professional curriculum system with "broad foundation, strong core, and emphasis on practice" based on the enterprise's job competency model. Combined with the professional positioning and characteristics of the school, the main courses and practical courses of the artificial intelligence major are set up by semester from the professional foundation, professional core, practical teaching, graduation project and other aspects , and the school and the enterprise jointly formulate a talent training plan integrating industry and education.

School-enterprise cooperation model
Schools and enterprises reconstruct teaching plans according to the OBE concept and innovate the "2.5+1.5" talent training model. Enterprises participate in the entire teaching process, implement teaching plans in stages, embed enterprise courses and practical training, and improve professional qualities and skills.

The construction of teaching resources
takes professional construction as the core, selects core professional courses, and constructs course resources that combine theory and practice and are oriented to practical ability, covering diversified content such as curriculum standards and teaching plans.

Jointly build a practical teaching system
Both schools and enterprises will leverage their respective industrial and educational resource advantages to improve the construction of a software engineering practical teaching system, including laboratory construction, training base construction, and practical teaching curriculum, to provide students with sufficient practical opportunities and experimental conditions. .

Innovation and entrepreneurship base construction
Schools and enterprises cooperate to build a mass entrepreneurship and innovation base, providing universal mass entrepreneurship and innovation courses, practice spaces, project case libraries, incubators and other resources, as well as management and big data platforms, to create a comprehensive mass entrepreneurship and innovation education service system.

The dual-qualified teacher training
relies on Neusoft's platform resource advantages in education, industry, and scientific research to develop a comprehensive teacher training system to improve teacher management, teaching and skill levels, and achieve accurate, efficient and high-quality development.