Program Curriculum
Master's Degree – Statistical and Informatics Technology
1. Program Objectives
The Master's program in Statistical and Informatics Technology aims to provide students with advanced scientific knowledge and high-level practical skills that enable them to analyze data, support decision-making, and contribute effectively to community development.
The main objectives of the program are:
- Prepare qualified graduates to work in various sectors of society and contribute to addressing poverty and unemployment through statistical analysis and the development of development programs.
- Advance scientific knowledge in statistics and informatics and their applications in science, technology, medicine, and business.
- Develop scientific research skills, including data collection, data analysis, and the preparation of high-quality scientific reports.
- Improve the quality of higher education by preparing qualified academic and research professionals capable of teaching and conducting scientific research.
Academic and Professional Excellence
The program seeks to integrate advanced theoretical foundations with modern practical applications, enhancing students' ability to analyze real-world problems, provide data-driven solutions, and support institutional innovation.
2. Duration and Study System
The Master's program in Statistical and Informatics Technology extends over two academic years.
- The first academic year follows the coursework system, with courses offered across two academic semesters.
- The second academic year is dedicated to preparing the Master's thesis and completing the requirements for its academic defense.
3. Graduation Requirements
Students are required to successfully complete 11 courses, amounting to 20 credit units, in addition to preparing a Master's thesis in a subject related to the program's specialization, worth 12 credit units. The total graduation requirement is 32 credit units.
A student who fails to pass a course is permitted a second examination attempt. If the student fails the course again, admission to the program will be terminated in accordance with the regulations and instructions approved by the Ministry of Higher Education and Scientific Research.
4. Learning Outcomes and Acquired Skills
- Perform advanced statistical analysis and quantitative modeling.
- Apply statistical and informatics techniques to address real-world problems.
- Conduct independent scientific research and prepare academic theses and reports.
- Develop analytical thinking and data-driven decision-making skills.
- Keep pace with modern technological developments in data analysis.
- Contribute to economic development and support innovation and new projects.
5. Learning Environment and Course Assessment
The learning environment of the Master's program in Statistical and Informatics Technology provides an integrated educational experience that supports both theoretical and practical learning. Courses are delivered in Arabic and English, using face-to-face instruction and e-learning when necessary. Scientific references and specialized readings are also provided to strengthen students' understanding of advanced statistical concepts and their modern applications.
The learning environment includes:
- Face-to-face lectures in classrooms.
- Use of e-learning technologies and digital platforms.
- Access to computer laboratories to support practical learning.
- Use of recent scientific sources and references in statistics and informatics.
Course assessment follows a comprehensive and balanced system that includes:
- Scientific assignments and exercises.
- Midterm examinations.
- Practical activities conducted in classrooms or laboratories.
- Projects and short research assignments.
- Final examinations at the end of each semester.
This assessment system aims to measure students' academic progress and develop their analytical and research capabilities in an integrated manner.
6. Study Plan – First Academic Year / First Semester
| No. | Course Name | Credit Units |
|---|---|---|
| 1 | Statistical Inference | 3 |
| 2 | Design of Agricultural Experiments | 3 |
| 3 | Randomization | 3 |
| 4 | Scientific Research Methodology | 2 |
| 5 | Big Data and Artificial Intelligence Using R (Elective) | 3 |
| 6 | English Language | – |
| Total | 14 |
Study Plan – First Academic Year / Second Semester
| No. | Course Name | Credit Units |
|---|---|---|
| 1 | Multivariate Analysis | 3 |
| 2 | Time Series Analysis | 3 |
| 3 | Advanced Mathematics | 2 |
| 4 | Biostatistics / Nonparametric Methods (Elective) | 3 |
| 5 | Linear and Nonlinear Models | 3 |
| Total | 14 |
Second Academic Year – Master's Thesis
The second academic year is dedicated to preparing the Master's thesis in a specialized field related to Statistical and Informatics Technology. During this stage, students conduct independent scientific research, collect and analyze data, interpret research findings, and prepare the final thesis for academic evaluation and defense.
Credit units allocated to the Master's thesis: 12.
7. Summary of Credit Units According to the Published Course Tables
| No. | Academic Component | Credit Units |
|---|---|---|
| 1 | First Semester | 14 |
| 2 | Second Semester | 14 |
| 3 | Master's Thesis | 12 |
| Calculated Total Based on Published Tables | 40 |
8. Official Graduation Requirements
| No. | Graduation Requirement | Credit Units |
|---|---|---|
| 1 | Coursework | 20 |
| 2 | Master's Thesis | 12 |
| Total Graduation Requirements | 32 |