Program Overview

About Zayed University

Zayed University was awarded a 3-star rating by the Global Star Rating System for Services.

Academic Programs

Undergraduate Studies

• Undergraduate Programs
• Admission Criteria
• Tuition Fee and Scholarship
• Undergraduate Application
• ZU Catalog

Graduate Studies

• Graduate Programs
• Graduate Faculty
• Graduate Admissions
• Graduate Scholarships
• Course Catalog

University Registrar

• Introduction
• Academic Forms
• e-Services
• ZU Academic Passport
• Guidelines for new students
• FAQ Guides for Students

Colleges

• Colleges/Centers/Institutes
• College of Arts and Creative Enterprises
• College of Business
• College of Communication & Media Sciences
• College of Humanities and Social Sciences
• College of Interdisciplinary Studies
• College of Natural and Health Sciences
• College of Technological Innovation

Research

About ZU Research

• About ZU Research
• Funding Opportunities
• For Researchers
• For Students

ISER

• Introduction
• About ISER
• ISER Books and Reports
• ISER Working Papers
• Current Projects

Data Science

What is Data Science?

Data Science is an interdisciplinary field that extracts insights and knowledge from data using statistical techniques, machine learning, data mining, and data visualization.

Key Applications of Data Science at ZU

• Predictive Analytics: Using AI/ML models to identify at-risk students and predict graduation rates.
• Sentiment Analysis: Using tools like Blue ML to analyze unstructured communication data, such as student comments, and extract actionable insights.
• Trend Prediction: Predicting future job market trends by analyzing job vacancies and in-demand skills to align educational offerings.
• Ranking Prediction: Leveraging predictive analysis of key ranking-related metrics to predict ZU's placement in future rankings.
• Resource Optimization: Optimizing resources by analyzing patterns and trends.

Data Science Use Cases at ZU

• Predicting 'At-Risk' Students: AI/ML models assign a 'risk' score to students, helping identify those who may require additional support.
  • Uses data from 2016 onwards, structured by Term and overall students.
  • Employs the Azure Machine Learning Workspace.
  • Achieves greater than 88% accuracy in predicting at risk students.
• Prediction of Years of Graduation: AI/ML models predict the number of years a student will take to graduate, aiding in forecasting graduation rates.
  • Uses data from 2016 onwards, structured at PIDM level.
  • Employs the Azure Machine Learning Workspace.
  • Achieves greater than 90% accuracy in predicting years of graduation.

Data Science Life Cycle

The data science life cycle includes the following stages:

• Business Understanding
• Data Mining
• Data Cleaning
• Data Exploration
• Feature Engineering
• Data Visualization
• Predictive Modeling

Benefits of Data Science

• Informed Decision-Making: Provides insights derived from data analysis, leading to more accurate and strategic decisions.
• Competitive Advantage: Identifies market trends, consumer preferences, and operational inefficiencies.
• Risk Management: Helps mitigate potential risks through data analysis.