There is a huge spike in number of computer science engineering graduated students who are unemployed or un- deremployed. This is the prime reason why mental health of young aged student (18-24) is also going down. It is also true that world is facing economic crisis. From student point of view, it is very important for them to be well planned and organized from initial stage of their academic. World of information technology is quite unpredictable and dynamic in nature. In present time, there are lot of specific jobs in this field which requires different level and combination of skills. In this research we are trying to analyze all academic details and skills of students at a time and then predict best matching jobs for students. The idea is to make them aware before final semester so that they can plan their study according to it and be hopeful, stress-free and happy in their life even if they are poor in some subjects. For this research data has been collected from reputed engineering colleges of Chennai. Data mining techniques are used to provide the analysis for the classification and prediction algorithms. The algorithms like Decision Tree, Random Forest has been used here which generate most accurate model in which after feeding level of academic details and skills of students is suggesting best matching jobs for them. The core idea behind this research is to visualize the trends of previously placed students and match it with skills of students who are in current academic session and then determine most suitable jobs according to their skills and help them in living stress free life.

Decision Tree. Random Forest. Data mining