How colleges and universities should set up relevant majors and guide employment in combination with market demand has always been a hot topic in the discussion of college employment. The eternal principle is that the establishment of colleges and universities cannot be too far away from market demand. The best combination is that colleges and universities are forward-looking and can be one step ahead of the market, so as to cultivate future talents and serve the future market.
The problem currently encountered by colleges and universities is that in the talent training mode, colleges and universities often ignore the real employment needs of the market, pay too much attention to theoretical teaching, and ignore the cultivation of students' ability to face real business projects. Practical ability and project thinking make it impossible for students to find jobs that match their career plans in the real job market, and companies cannot find a digital talent pool with real hands-on capabilities.
How to break the predicament of colleges and universities, based on more than ten years of practical experience in the data intelligence industry, focusing on the direction of big data and artificial intelligence, summed up the following methods to improve the employment quality of colleges and universities and help students get rid of the dilemma of employment difficulties.
1. Establish a big data laboratory
The overall goal of laboratory construction is to build a one-stop teaching service platform. The concept of a one-stop teaching service platform is proposed on the basis of a deep understanding of the discipline construction and existing problems in colleges and universities. Focusing on all aspects of discipline construction, it provides a complete product system from major establishment, curriculum setting, teacher training, teaching resources, experimental environment, student training and practice, employment and entrepreneurship, etc., to meet the requirements of different stages of discipline construction and talent training in universities need.
The big data laboratory provides teaching and training resources, teaching and training platforms, and provides teaching services.
While cultivating students' hands-on ability, it also provides integrated data analysis and application solutions from modeling to application for scientific research, empowers scientific research applications in colleges and universities, and helps teachers quickly implement the application of scientific research results.
2. Strengthen the strength of the teaching staff.
College teachers have long focused on teaching and research in professional fields. When facing emerging industries such as big data and artificial intelligence, it is inevitable that they will be out of touch with the actual industry. In the face of this situation, colleges and universities can actively cooperate with enterprises, organize professional teacher training courses jointly with enterprises, organize teaching teams to go deep into the front line of enterprise business, and provide teachers with teaching methods that combine cutting-edge theoretical knowledge with relevant real cases. Efficient lesson preparation and smooth teaching of relevant professional courses have laid a solid foundation, which ultimately improves teachers' engineering practice ability and teaching level, and promotes professional teaching reform.
In 2023, Teddy Intelligent Technology organized eight special trainings for teachers, including:
1. Data collection and processing practice (Python)
2. Business data analysis practice (Excel+Power BI)
3. Big data analysis and machine learning practice (Python)
4 , Network public opinion and sentiment analysis actual combat (Python)
5. PyTorch and artificial intelligence actual combat,
6. Computer vision application actual combat (PyTorch),
7. Computer vision application actual combat (TensorFlow),
8. Natural language processing actual combat (TensorFlow)
school-enterprise cooperation The significance lies in the win-win situation between the school and the enterprise, helping students to go out better. Guided by the needs of industrial talents and aimed at cultivating practical talents, schools and enterprises make full use of their respective superior resources to carry out multi-faceted cooperation and jointly build a big data practice base. On the one hand, it provides students with a good practice environment and training projects. At the same time, corporate engineers and university teachers jointly carry out training projects to improve students' overall practice level and social competitiveness, and ensure the standards and standards of big data-related talent training. quality. And through the benign interaction between universities and enterprises, create good conditions for students' internship and employment, guarantee students' internship and employment, and let students "go out" during the professional internship stage of students, truly participate in the project practice of enterprises, and understand the specific business application How to use big data knowledge to solve specific problems, provide students with practical application ability, and accumulate industry project experience. Really participate in the practice of the enterprise, further understand the industry norms of the enterprise, and enhance the practical ability.