College of Computing and Informatics

College of Computing and Informatics

College of Computing and Informatics

Introduction

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

4 semesters.

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

  • .The Master of Data Science program contains 12 courses, three credit hours each, distributed over four semesters.
  • .The program is only offered in English.

Coding ​ Course Name Credit Hours Prerequisite​
Level One
CS501 Research Methods in Computational Studies 3
DS510 Statistics for Data Science 3
DS540 Advanced Python for Data Science 3
Level Two
DS520 Big Data Processing and Analytics 3
DS630 Artificial Intelligence for Data Science 3
DS560 Advanced Data Mining 3
Level Three
DS610 Advanced Applied Statistics for Data Science 3
DS620 Data Visualization 3
DS550 Machine Learning Algorithms for Data Science 3
Level Four
DS650 Predictive Analytics for Business 3
DS660 Deep Learning Techniques 3
DS698 Capstone Project in Data Science 3