Program Introduction
Data Science is considered one of the most exciting fields of the twenty-first century due to the rapid growth in internet usage, social media applications, and the Internet of Things. We now have massive amounts of data that are difficult to manage and analyze using traditional statistical methods, which is why Data Science is often referred to as the “oil of the twenty-first century."
Applying modern sciences and artificial intelligence techniques to analyze data and extract knowledge patterns has become one of the greatest challenges of our time. The labor market still suffers from a severe shortage of qualified professionals to meet the demand in this field. Therefore, the College of Computing and Informatics at the Saudi Electronic University offers a comprehensive Master’s program in Data Science, built and prepared according to global standards using the latest methodologies to equip professionals to successfully and creatively face major challenges in the field of Data Science.
- Achieve a balance between theoretical study of data science and practical, applied aspects.
- Develop academic and professional skills in data science and big data analysis.
- Prepare professionals for applied fields in data science, as well as for students’ self-development and continuous learning.
- Apply best practices to create a comprehensive project management plan.
- Equip professionals to meet labor market demands in areas requiring data science skills across various sectors.
- Hold a Bachelor’s degree from a recognized university. If the degree is from abroad, it must be equivalently accredited according to the Ministry of Education’s equivalency program.
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The cumulative GPA in the Bachelor’s degree must be at least 2.00 out of 4.00 or 3.00 out of 5.00, or its equivalent, based on admission competition and seat availability. The College Council may grant an exception, provided the GPA is not less than 1.5 out of 4.00 or 2.5 out of 5.00, or its equivalent, based on admission competition and seat availability.
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Submit a result from one of the approved English language tests:
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IELTS-Academic: minimum score of 5
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STEP: minimum score of 76
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TOEFL IBT: minimum score of 45
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Exemptions:
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Graduates of the Saudi Electronic University programs taught in English with a cumulative GPA of at least 3.5 out of 4.00 or higher.
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Applicants who hold a Bachelor’s degree from a university in a country where English is the native language* and the university is recognized by the Ministry of Education.
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Language test results must not be older than:
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TOEFL IBT: 2 years
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STEP: 3 years
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IELTS-Academic: 3 years
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Only one language test result is required.
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Accepted Bachelor’s specializations: Computer Science, Computer Engineering, Information Systems, Software Engineering, and Information Technology.
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Applicants must be Saudi or non-Saudi residents living in the Kingdom of Saudi Arabia.
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Preliminarily accepted applicants are required to pay the tuition fees for the first semester to obtain final admission.
*Countries: USA – Canada – UK – Australia – New Zealand
- Develop algorithms and computational and statistical models in data science.
- Extract, transform, integrate, and load large datasets.
- Evaluate opportunities to apply data science solutions for predictions and analytics in various business systems.
- Coordinate the use and application of descriptive, predictive, and prescriptive analytics principles to address different challenges.
- Develop deep learning programs to support the analysis of complex datasets.
- Distinguish between key theories of machine learning and neural networks.
- Represent and visualize data for exploration, analysis, and clear communication of information.
- Use machine learning and optimization models to support decision-making.
- Apply problem-solving strategies in data analytics.
- Present analytical conclusions and recommendations in written form and through visual charts.
- Integrate multiple computational processes to support data science using widely applied tools and software.
- Understand managerial, ethical, and information privacy challenges in data science.
- Statistical Systems Analyst
- Data Manager
- Computer Systems Analyst
- Data Scientist
- Software Developer
- Data Analyst
- Big Data Engineer
- Financial Data Analyst
- Machine Learning Systems Engineer
- Data Director
- Intelligent Business Systems Engineer
- Big Data Systems Manager
- Data Mining Analyst
- Data Engineer
- Big Data Systems Designer
- Data Visualization and Representation Developer
