1.As a member of the development team at Gozine2 Institution of Education and Culture, I contributed to the creation of a stream rank estimation program designed to accurately estimate the ranks of up to 50,000 students. The program utilized sophisticated data mining techniques and mathematical algorithms to generate reliable and accurate results.My role in this project involved developing key components of the program, testing and debugging code, and collaborating with other team members to ensure that all aspects of the program were functioning as intended. Through my work on this project, I gained invaluable experience in software development and data analysis, and was able to contribute to the creation of a highly effective tool for assessing student performance.2. Recommender System Development: Conducted data cleaning and preprocessing using Python and SQL, developed a similarity matrix with scikit-learn, and created a recommender system using collaborative filtering techniques. This system suggests similar questions to those students answered incorrectly, enhancing targeted practice.3.Pre-IRT(Item Response Theory) data analysis: Engineered a program to analyze student performance data, identifying individual strengths and weaknesses, and assessing the difficulty of each question based on student responses. This analysis contributed to more effective study strategies. 4.Constraint analysis: Analyzed the major selection system by identifying and extracting complex constraints such as gender-specific requirements, city residency rules, post-graduation work conditions, etc. Developed prediction models to help students estimate potential university admissions based on their ranks, considering both university capacities and additional eligibility factors.