Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/2837
Title: Admission Intelligence
Authors: Khan, Hassan
Ramzan, Tamoor
Hassan Abbas, Syed
Keywords: Academic career
Academic orientation
BS Thesis
Issue Date: 2017
Publisher: University of Management and Technology
Abstract: Admission Intelligence (AI) provides a simple interface for students and institutes to help them. The basic purpose of this system is to help student in a way that make them ease to decide where to get admission. This system will asks for input from the user that may involves educational record, current status, location and other requirements. Once, system will have all the information it will generate a particular output based on previous history of institutes, like expected criteria, fee, duration and other resources. The creation and management of accurate, up-to-date information regarding a students’ academic career is critically important in the university as well as colleges. Admission Intelligence system deals with all kind of student details, academic related reports, college details, course details, curriculum, batch details, placement details and other resource related details too and also a forum where anyone can participate in critics going on or can share his/her experience. It tracks all the details of a student from the day one, when it gets registered with the system and later helps him to decide or guide where to go. It can be used for all reporting purpose, the current status of the institute in respect of ranking or market value, curriculum details, fee details, project or any other necessary details and all these will be available through a secure, online interface embedded in our website. It will also have faculty details, batch execution details, students’ details in all aspects. It also facilitate us explore all the activities happening in the college, different reports and queries can be generated based on vast options related to students, batch going on or the field.
Description: Supervised by: Amjad Hussain Zahid
URI: http://hdl.handle.net/123456789/2837
Appears in Collections:Department of Computer Science

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