In view of the employment difficulties of college graduates, this paper analyzes the overflow of graduates in a particular period caused by the expansion of enrollment in various colleges and universities and the social phenomenon of social positions in short supply. First, the employment status of application-oriented college students and the deficiencies of employment guidance courses are summarized. Then, deep learning technology is combined with the relevant employment concept to construct an employment training model to guide college students in employment. Besides, a questionnaire on learning effect and employment quality is designed from four perspectives: learning motivation, concentration, teaching process, and final results. The information collected through the questionnaire demonstrates that the employment quality and learning effect of male and female students are not significantly affected by gender differences. In addition, the P values of learning motivation, concentration, and teaching process are all less than 0.01, and the unstandardized coefficient of the teaching process is 0.349, which has the most significant impact on the learning effect. In short, the three factors positively affect the learning effect. Therefore, it comes to the conclusion of improving the ability and strategy of classroom employment guidance. If one wants to be successful in job hunting and career selection, it is not enough just to be competitive but also to be good at it. Being good at the competition is reflected in having good psychological quality, strength, and a good competitive state. In the job hunting and career selection competition, attention should be paid to whether the expected value is appropriate. College students should have sufficient self-awareness before preparing to submit resumes. During the interview, they should overcome emotional anxiety. If a person can treat study, work, and life in a good mood from beginning to end, he will win the competition. The research reported here can provide some reference suggestions for the employment quality of application-oriented college graduates.