In November 2021, the 25th AI training course for college teachers jointly organized by Baidu and the Education Guidance Committee of the Ministry of Education was officially launched, and more than 100 front-line backbone teachers from 74 colleges and universities across the country participated in the training of artificial intelligence knowledge and practice courses. Wei Jiangjiang, Director of the Computer and Information Bureau of Tsinghua University Press, Professor Gao Xiaopeng, Deputy Secretary-General of the Steering Committee for Computer Science Teaching in Colleges and Universities of the Ministry of Education, and Liu Qian, General Manager of Baidu AI Technology Ecology Department, attended the ceremony.
Gao Xiaopeng said at the opening ceremony that for new engineering education, the most important thing in domestic artificial intelligence teacher training is to combine theory and practice, carry out practical teaching, and help teachers return to school to open courses.
Up to now, Baidu has trained more than 3,000 front-line teachers in more than 700 colleges and universities to teach AI courses, helping teachers optimize AI-related professional courses and student practice application platforms to improve teaching quality.
According to the 14th Five-Year Plan of the People's Republic of China, artificial intelligence is the main field of new infrastructure, and the demand for artificial intelligence talents in the current society is constantly rising. However, in the face of the talent gap, the school has two major pain points in the training of AI talents: insufficient teaching staff and lack of AI practice platform.
A number of university leaders said that now the university not only can not quickly expand the artificial intelligence professional teachers, but also face the problem of teacher talent loss, many college teachers choose to leave the campus to enter the enterprise. Teachers who stay on the front line to teach artificial intelligence also have difficulties, and if the class only talks about technical knowledge, students will feel bored, let alone digestion and application. Moreover, there are very few underlying data samples for AI development experiments, and there is no way to support the development of experiments. To solve the "bull nose" problem of the shortage of artificial intelligence education teachers, the focus is to amplify the productivity of existing teachers, and at the same time strengthen industry-university-research cooperation with science and technology enterprises to solve the problem of lack of projects. (Wen Lee)
Source: Guangming Network
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