Data Science / Research Projects
Forecasting
Prediction of future enrollments developed by comparing actual enrollments through time to identify the trends and predict future outcome within a range of confidence
- Enrollment projections based on real-time deposit activity
- Predictive Analytics
- Time Series
- Inferential Engine
- Multilevel modeling (MLM)
Developed a program in R to model the prediction of UG student enrollment by different majors and clusters
Developed analytical reports through reproducible and transparent programs using SPSS syntax
Forecasted graduate enrollment and seats demand through a mathematical model in SQL queries
Developed complex SQL queries to generate prediction indicators like “Time_to_Graduate”
Conducted a research on AUB applicants analysis to predict long-term Enrollment and credit hours using regression models
Conducted Enrollment forecasting at the faculty level using Time Series technics E.g. Exponential smoothing with 95% CI.
Systematic Analysis
Two group analysis
Profile analysis
Data Envelopment Analysis (DEA)
Inferential statistics
Regression model
Elasticity estimates
Conducted a statistical profile analysis on the characteristics of new accepted AUB enrolled students vs accepted but not-enrolled students including yield enrollment analysis
Compared metrics between retained vs. non-retained students
Estimated the probability of attrition (or effect on first term GPA) on freshmen and sophomores students based on multiple variables/risks
Conducted regression on student performance in their 1rst year
Built dynamic tables with SQL coding for better analytics and prediction
Research
My Post-Graduate Diploma in Data Science has given me the right exposure to a broad range of data models that helped me in my research projects.
- Published an article entitled “Data Science Project Management Framework (DSPMF)” dealing with the proper project management processes and practices in exploratory Data Science projects
- Developed various Machine Learning-based tools and processes while providing insights into university data
- Researched on the post-audit phase of ERP implementation using the notion of “workarounds”