Date of Publication :10th May 2021

Abstract: Placement is the high-ranking initiative of any institute. During the placement process there are major three parts (a) Training (b) Placement administration (c) Suitable Placement. After this process the key point is does the students are satisfied with their placements? With respect to IT-Jobs, the job satisfaction changes frequently. But when an institute place some student at a company, it is very important for the institute to analyze that how many students are satisfied with their placements? Which Companies should get priority at on-campus, which companies should be invited for off-campus, which companies are there who deals with mass-students, which companies are there who deals with skills of students, what kind of training module do these companies are offering, what would be the lower and upper limit of the package offered by companies and how many companies should be invited for the placements in single session. These all parameters take place after the session of placement ends in the final year batch. These parameters can be common for wide streams but the result would be very-very different and very according to stream and market requirement. Thus it is required to perform this analysis after each session which can be conducted as post-placement analysis. This Paper represents the post-placement Analysis for Institute based in Gujarat (*not to mention name) for MSc-CA & IT program, which is performed on the dataset of “Placemet-2019-20” using Correlation in python between ‘students rating for training at companies and Package offered by the companies.

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