Contact UsIntroduction
The College of Computing and Informatics offers Master of Science in Data Science program that aims to qualify students with high academic skills in aspects related to data science and usage of data analysis software, providing students with the latest tools and methods in big data technologies for the next generation. The program focuses on combining the cognitive and applied aspects in the field of data science, machine learning and artificial intelligence; and practically apply these technologies in problem solving.
The Importance and Reasons for Creating the Program
-Data science is considered as the most exciting specialty in the twenty-first century, as a result of the great development in usage of Internet technologies, social networking applications and the Internet of things, therefore, we now have huge amounts of data that are difficult to handle and analyze by the traditional statistical methods. Thus, the specialty of data science has become called the oil of the twenty-first century.
-The application of modern science and artificial intelligence techniques to analyze data and extract knowledge patterns has become one of the biggest challenges in the current century. The labor market is still suffering from a severe shortage of qualified personnel to meet the need for work.
-Therefore, the College of Computing and Informatics in the Saudi Electronic University presenting an integrated program for the Master of Data Science, which was built and prepared according to international standards and conform with the latest techniques and methods to qualify students to meet the major challenges in the field of data science successfully and creatively.
Program Objectives
1- Balance between data science studies theory and practical work.
2- Develop both academic and professional skills in the domain of data science and big data analytics.
3- Prepare learners for the data science profession or continued study.
4- Implementing best practices to develop comprehensive project management plan.
5- Prepare the learner to meet the business needs in areas where data science skills are required in various sectors.
Duration of Study in the Program
Thress semesters for the Pre-Master Data Science Program, and 6 semesters of MSc Data Science.
Program Learning Outcomes
1- Develop algorithmic, computational, and statistical models in data science.
2- Extract, transform, integrate, load, and access large data sets.
3- Evaluate opportunities to employ data science solutions for business forecasting and analytics.
4- Synthesize principles of descriptive, predictive, and prescriptive analytics to address challenges.
5- Create deep learning programs to support the analysis of complex datasets.
6- Differentiate between the major theories of machine learning and neural networks.
7- Visualize data for exploration, analysis, and communication.
8- Use machine learning and optimization models to decision making.
9- Apply problem-solving strategies to data analytics.
10- Articulate analytical conclusions and recommendations in written and visual formats.
11- Assemble computational pipelines to support data science from widely available tools.
12- Understand management, ethical, privacy, and accountability issues in data science.
Career Opportunities for Graduates of the Program
1- Statistician
2- Data Administrator
3- Computer Systems Analyst
4- Data Scientist
5- Software Developer
6- Data Analyst
7- Big Data Engineer
8- Financial Data Analyst
9- Machine Learning Engineer
10- Data Manager
11- Business Intelligence Engineer
12- Big Data Administrator
13- Data Mining Analyst
14- Data Engineer
15- Big Data Architect
16- Data Visualization Developer
Introductory Chapter
| First Semester | |||
| Course Code | Title | Hours | Prerequisites |
| DS502 | Object Oriented Programming | 3 | |
| DS504 | Mathematics for Computer Science | 3 | |
| DS505 | Introduction to Database | 3 | |
| Second Semester | |||
| Course Code | Title | Hours | Prerequisites |
| DS503 | Operating Systems | 3 | - |
| DS506 | Data Structure | 3 | DS502 |
| DS507 | System Analysis & Design | 3 | DS505 |
| Third Semester | |||
| Course Code | Title | Hours | Prerequisites |
| DS508 | Data Mining and Data Warehousing | 3 | DS505 |
| DS509 | Decision Support Systems | 3 | DS505 |
- The Master of Data Science program holds 12 subjects, of which three are credit hours, spread over six semesters.
The program is only available in English.
| Coding | Course Name | Credit Hours | Prerequisite |
|---|---|---|---|
| Level One | |||
| CS501 | Research Methods in Computational Studies | 3 | |
| DS540 | Advanced Python for Data Science | 3 | |
| Level Two | |||
| DS560 | Advanced Data Mining | 3 | |
| DS510 | Statistics for Data Science | 3 | - |
| Level Three | |||
| DS520 | Big Data Processing and Analytics | 3 | DS510 & DS540 |
| DS630 | Artificial Intelligence for Data Science | 3 | DS540 |
| Level Four | |||
| DS550 | Machine Learning Algorithms for Data Science | 3 | DS520, DS630 |
| DS610 | Advanced Applied Statistics for Data Science | 3 | DS510 |
| Level Five | |||
| DS620 | Data Visualization | 3 | DS560 |
| DS660 | Deep Learning Techniques | 3 | DS630 |
| Level Sixth | |||
| DS650 | Predictive Analytics for Business | 3 | DS560, DS610 |
| DS698 | Capstone Project in Data Science | 3 | Department Approval |
To view the study plan files
Master of Science in Data Science Click Here
Transfer Conditions from Inside the University to Master of Science in Data Science Program Click Here
Pre-Master Data Science Program
Introduction
The College of Computing and Informatics at the Saudi Electronic University offers a Pre-Master program to qualify non-specialists who hold a bachelor’s degree in Science or Administration; or graduated from Technical Collages to provide them with basic knowledge and skills to enable who passed this Pre-Master Program to join the Master of Data Science Program. This program aims to qualify students with high academic skills and aspects related to data science and usage of data analysis software, with an interest in providing them with the latest means, tools, methods related to the future of big data and its processing, as the program focuses on combining the cognitive and applied aspects in the field of data science, machine learning and artificial intelligence; and utilizing technology in solving various problems in all areas of life.
The Importance and Reasons for Creating the Program
- Data analysis using artificial intelligence techniques in various fields and deriving patterns of knowledge have become one of the biggest challenges of the current century. The labor market is still suffering from a severe shortage of qualified cadres to meet the need for work in this field.
- The data science major provides scientific solutions to various sectors that require mastery from specialists in those sectors.
- Therefore, the College of Computing and Informatics at the Saudi Electronic University offers this Pre-Master Program for non-specialists to enable them to acquire the basic skills that must be mastered before starting the Master of Science in Data Science Program, which was built and prepared according to international standards and conform the latest techniques and methods to qualify cadres to face major challenges in the data science field successfully and creatively.
Program Objectives
1- Providing students with the basic skills required for the Master of Science in Data Science Program.
2- Develop students' academic skills and make them aligned with the Master of Science in Data Science Program requirements.
3- Bridging the knowledge gap for non-specialized students who intend to study in the Master of Science in Data Science Program.
Duration of Study in the Program
Two semesters.
Program Learning Outcomes
1. Learn advanced programming techniques such as inheritance and polymorphism
2. Ability to analyze and develop software.
3. Introduce students to different computer operating systems and their functions.
4. Designing different databases and identifying the most important concepts and technologies associated with databases, such as networks and the Internet.
5. Store and retrieve data using various data structures.
6. Learn about smart systems and their role in the decision-making support process.
Admission Requirements for the Pre-Master Program
- The admission requirements stated in The Unified Regulations for Postgraduate Studies in Saudi Universities (click here)
- The Bachelor degree should be in: computer, scientific, administrative, or technical colleges.
-
The cumulative GPA in the bachelor's degree should not be less than (2.00 out of 4.00 or 3.00 out of 5.00).
Equivalency of Courses from the Bachelor's Program
Students can equate four courses (a maximum of the pre-master program courses) with courses they have passed at the undergraduate level with the following conditions :
1- Submitting the equivalency request via the system during the announced period for equivalency.
2- Submitting evidence of studying the course at the bachelor's program in English.
3- The university at which the bachelor's degree was studied should be recognized by the Ministry of Education.
4- The grade of the course to be equivalent must be (good) or higher.
5- The course should be studied in a regular or blended education style.
6- The course specification of the course to be equivalent must match the equivalent SEU course.
7- The course to be equivalent should be passed during the last five years, not before that.
8- Submitting detailed course specifications of the courses to be equivalent, certified by the university in which the courses were studied.
Admission Requirements for the Master of Science in Data Science
1. Bachelor's degree from a MOE-recognized university. If the certificate is obtained from abroad, it must be accredited according to the equivalency program provided by the Ministry of Education (MOE).
2. Have a cumulative GPA in the bachelor’s degree should not be less than (2.00 out of 4.00 or 3.00 out of 5.00). The College Council may waive this condition provided that the applicant's GPA is not less than (1.5 out of 4.00 or 2.5 out of 5.00) or its equivalent.
3. Submit the result of one of the approved English language tests:
- IELTS-Academic only: with a score of no less than 5
- STEP: with a score of no less than 76
- TOEFL_IBT: with a score of no less than 45.
SEU graduates are exempted from this condition provided that their bachelor’s program was taught in English, and a with a cumulative GPA of no less than (3.5 out of 4.00) or higher.
Students who have obtained a bachelor’s degree from universities in countries where the native language is English* and the universities are recognized by the Ministry of Education are exempted.
4. The validity period of the approved English language tests:
- TOEFL_IBT: 2 Years
- STEP: 3 Years
- IELTS Academic only: 3 Years
Applicants need to submit only one English language test.
5. Accepted Bachelor's majors: Computer Science, Computer Engineering, Information Systems, Software Engineering, and Information Technology.
6. Applicants holding non-IT degrees can apply for admission after passing the Pre-Data-Science program. However, the applicant has to have a bachelor degree in a scientific, management or theoretical field, or Bachelor’s degree graduates from technical colleges.
7. Applicants who have been initially accepted, are required to pay the full amount of first semester tuition to get final admission.
Study Plan
The Pre-Master of Data Science Program contains eight courses, three credit hours each, distributed over two semesters.
English is the Medium of Instruction in the Program
Study Plan Structured by Semesters
| First Semester | |||
| Course Code | Title | Hours | Prerequisite |
| DS502 | Object Oriented Programming | 3 | |
| DS504 | Mathematics for Computer Science | 3 | |
| DS505 | Introduction to Database | 3 | |
| Second Semester | |||
| Course Code | Title | Hours | Prerequisite |
| DS503 | Operating Systems | 3 | - |
| DS506 | Data Structure | 3 | DS502 |
| DS507 | System Analysis & Design | 3 | DS505 |
| Third Semester | |||
| Course Code | Title | Hours | Prerequisite |
| DS508 | Data Mining and Data Warehousing | 3 | DS505 |
| DS509 | Decision Support Systems | 3 | DS505 |
