In the context of big data, the era of educational informatization has fully arrived, making the influence of information technology on language disciplines not to be underestimated. This has promoted vocational English teaching from the original slide multimodal demonstration teaching to the multimodal teaching stage relying on micro courses, playing a good synergistic role in improving English teaching classrooms, innovating teaching reforms, and improving students' English listening, speaking, reading, and writing abilities.

Under the background of the continuous development of science and technology, the era of big data has come in an all-round way, and big data technology has also been widely used in the education industry. The course of financial management in applied colleges and universities is a highly applied course, which focuses on the substance of the course. Teachers need to create a good learning environment for students with the help of information technology, and constantly cultivate students' professional skills and professionalism. In order to improve the quality of financial management courses in colleges and universities, this paper mainly analyzes the management courses in application-oriented colleges and universities, expounds the factors affecting the practical teaching quality of management courses in colleges and universities, and analyzes the teaching methods of management courses in application-oriented colleges and universities. Finally, it is concluded that only when teachers constantly improve their teaching level, can students' learning level be improved by combining theory with practice.

Targeted Poverty Alleviation refers to the targeted funding work completed in the process of higher education development. However, at present, in the process of implementing the requirements of Targeted Poverty Alleviation in China's universities, some students' families are difficult to complete identification, and there are also some problems in the information management of the funders, which has seriously affected the funding for students with financial difficulties in their families during the period of higher education in China. With the rapid development and progress of Big data technology, through the establishment of a sound information technology system, we must help students actively change the funding model in the future and greatly improve the funding, which is of great significance to the development of university funding supervision and management.

Under the background of the development of the network information age, the current Internet industry has obtained more development opportunities, but it has also brought corresponding challenges in the process of wide application. In the development and construction of modernization, society pays more attention to the supervision and determination of the characteristics of online public opinion. From the perspective of the current characteristics of network public opinion, because social information is more extensive and involves many fields, network public opinion has a high degree of complexity and diffusion. Therefore, it is necessary to strengthen the analysis and application of relevant data mining systems in order to achieve efficient management of network public opinion. The key to the disadvantage of the traditional excavation of public opinion communication characteristics lies in the lag of the excavation process, and it is difficult to deal with malignant public opinion in a timely and effective manner. Therefore, in order to truly solve the lagging problem of public opinion data dissemination feature mining technology, it is necessary to strengthen the application of artificial intelligence technology in it.