  A career is a crucial aspect for any person to fulfill their desires through
hard work. During their studies, students cannot find the best career
suggestions unless they receive meaningful guidance tailored to their skills.
Therefore, we developed an AI-assisted model for early prediction to provide
better career suggestions. Although the task is difficult, proper guidance can
make it easier. Effective career guidance requires understanding a student's
academic skills, interests, and skill-related activities. In this research, we
collected essential information from Computer Science (CS) and Software
Engineering (SWE) students to train a machine learning (ML) model that predicts
career paths based on students' career-related information. To adequately train
the models, we applied Natural Language Processing (NLP) techniques and
completed dataset pre-processing. For comparative analysis, we utilized
multiple classification ML algorithms and deep learning (DL) algorithms. This
study contributes valuable insights to educational advising by providing
specific career suggestions based on the unique features of CS and SWE
students. Additionally, the research helps individual CS and SWE students find
suitable jobs that match their skills, interests, and skill-related activities.
