MS Project Based Programs

Project-Based Master's Programs

Graduate Programs in Mathematics

King Fahd University of Petroleum & Minerals

Modeling and Simulation

Master of Science (Project-Based)

30
Credit Hours
2
Years
8
Core Courses
1
Project
About the Program

Modeling & Simulation is a rapidly developing field that brings together mathematicians, physicians, computer scientists, and engineers. It combines various topics from basic science, computer science, and engineering that lead to a better understanding and handling of complex phenomena. This interdisciplinary program is designed to provide knowledge and essential skills to deal with real-world applications in a wide range of industries. With such knowledge and skills, graduates will be capable of working and thinking more dynamically when it comes to solving challenging problems.

Key Focus Areas
Numerical Computing
Discrete & Fast Algorithms
Data Science
Inverse Problems
Statistical Models
Multi-Physics
Large Data Analysis
Program Highlights
01
Interdisciplinary Approach
Combines mathematics, computer science, and engineering to solve complex real-world problems
02
Applied Numerical Methods
Master finite element, finite difference, and finite volume methods for practical applications
03
Computational Multiphysics
Analyze multiple, simultaneous physical phenomena in fluid flow, heat transfer, and mechanics
04
Industry-Focused Project
Conduct real industry-based research project with technical presentation to experts

Data Science & Analytics

Master of Science (Project-Based)

30
Credit Hours
2
Years
8
Core Courses
1
Project
About the Program

Data continues to shape our today and tomorrow at an increasing pace. Every industry, government, social and health organization is developing smart and sophisticated analytical tools to draw meaningful insight from data to help their business and society. The Professional Master Program in Data Science and Analytics at KFUPM aims to prepare its graduates for careers in Data Science by offering an immersive multidisciplinary program that combines topics from Mathematics and Statistics with the tools from Computer Science.

Curriculum Coverage
01
Mathematical Foundations
Linear algebra, optimization methods, and mathematical foundations specifically for data science
02
Statistical Analysis
Probability theory, statistical inference, modeling, and time-series forecasting methods
03
Machine Learning & Deep Learning
Supervised and unsupervised learning, neural networks, CNNs, RNNs, and GANs
04
Big Data Technologies
Hadoop, Apache Spark, cloud computing, and advanced tools for large-scale data processing
05
Hands-On Experience
Develop advanced skills with modern software, toolboxes, and libraries used in industry
06
Capstone Project
Industry-based research project with real-world application and expert presentation

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