For the needs of professional layout adjustment and network ideological and political coordination optimization in universities under the background of digital economy transformation, this paper constructs an embedded intelligent optimization model of professional layout and network ideological and political, and completes the design of optimization method and system implementation. Aiming at the problems of demand response lag, separation of education orientation and insufficient decision support in the process of traditional major adjustment, this paper studies the integration of industrial demand, professional construction foundation, employment feedback, course operation status and network ideological and political resources into the unified computing framework, and forms a continuous mechanism of professional feature representation, ideological and political embedding recognition, optimization solution and feedback update. The experiment was based on the data of 12 universities in Fujian Province from 2020 to 2024, involving 72 undergraduate majors. After expanding by “Institution-Profession-year”, 864 samples were formed. The results show that the Accuracy of the proposed model on the test set is 89.3%, Macro-F1 is 87.6%, and AUC is 0.928, which is better than the comparison methods. The average response time of the system is 1.89 s under the condition of 250 concurrency, and the request success rate remains above 99.1%, which shows good stability and availability. The results show that this method can provide strong computing support and practical reference for the optimization of professional structure and network ideological and political construction in universities in the transformation of digital economy.
