Tuition Fee
Not Available
Start Date
Not Available
Medium of studying
On campus
Duration
2 years
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Details
Program Details
Degree
Masters
Major
Artificial Intelligence | Data Analysis | Data Science
Area of study
Information and Communication Technologies | Mathematics and Statistics
Education type
On campus
Timing
Full time
Course Language
English
About Program
Program Overview
Master's in Data Science
The Master's in Data Science program at the College of Computer Science and Information Technology is designed to meet the increasing demands of the industry. The program aims to graduate students with a solid foundation in data science, preparing them to compete successfully for high-demand jobs in the artificial intelligence sector.
Program Overview
- Duration: 2 years
- Total Credits: 45
- Study System: Regular
Admission Requirements
To be eligible for the Master's in Data Science program, applicants must:
- Hold a Bachelor's degree in Computer Science, a related field, Mathematics, or Statistics.
- Have a cumulative GPA of "Good" or higher.
- Have passed the General Aptitude Test for University Students.
- Have completed courses in Programming, Data Structures and Algorithms, Databases, Computer Networks, and Operating Systems as part of their Bachelor's degree.
- Demonstrate English language proficiency by either having completed their Bachelor's degree with English as the language of instruction or by submitting standardized test scores such as IELTS, TOEFL, or STEP.
Program Objectives
The Master's in Data Science program aims to:
- Equip students with the knowledge of statistical data analysis techniques used in decision-making.
- Apply data science principles to analyze business problems.
- Prepare students to understand and apply data science techniques and algorithms to achieve organizational goals.
- Enable students to solve problems involving large and diverse datasets from various application domains.
- Develop programming skills in data analysis, visualization, machine learning, and data mining.
- Qualify specialists with high competence in data science to work in the Saudi sector.
- Prepare students for career advancement in all fields of information science and technology.
Curriculum
Semester One
| Course Title | Prerequisite | Credits | Total Credits |
|---|---|---|---|
| Fundamentals of Data Science | - | 3 | 3 |
| Computational Mathematics | - | 3 | 3 |
| Programming for Data Science | - | 3 | 3 |
| Advanced Topics in Databases | - | 3 | 3 |
| TOTAL | 12 | 12 |
Semester Two
| Course Title | Prerequisite | Credits | Total Credits |
|---|---|---|---|
| Machine Learning | CSC641 | 3 | 3 |
| Research Methods | - | 3 | 3 |
| Data Mining | CSC641 | 3 | 3 |
| Data Visualization | CSC650 | 3 | 3 |
| TOTAL | 12 | 12 |
Semester Three
| Course Title | Prerequisite | Credits | Total Credits |
|---|---|---|---|
| Information Retrieval | CSC641 | 3 | 3 |
| Big Data Analytics | CSC640 | 3 | 3 |
| Seminar in Data Science | Completion of 18 credit hours | 3 | 3 |
| Research Project 1 | Completion of 21 credit hours | 4 | 4 |
| TOTAL | 13 | 13 |
Semester Four
| Course Title | Prerequisite | Credits | Total Credits |
|---|---|---|---|
| Data Science Professional and Ethical issues | - | 3 | 3 |
| Elective Course | Completion of 30 credit hours | 3 | 3 |
| Research Project 2 | CIS624 | 4 | 4 |
| TOTAL | 10 | 10 |
Elective Courses
| Course Title | Prerequisite | Credits | Total Credits |
|---|---|---|---|
| Text Analytics | Completion of 30 credit hours | 3 | 3 |
| Neural Networks and Deep Learning | Completion of 30 credit hours | 3 | 3 |
| Bioinformatics | Completion of 30 credit hours | 3 | 3 |
| Parallel Computing | Completion of 30 credit hours | 3 | 3 |
| Decision Support Systems | Completion of 30 credit hours | 3 | 3 |
| Selected topics in Data Science | Completion of 30 credit hours | 3 | 3 |
Career Opportunities
Graduates of the Master's in Data Science program can pursue various career paths, including:
- Data Analyst: Working in different sectors to analyze and interpret data for insights and valuable information.
- Machine Learning and Artificial Intelligence: Developing algorithmic models to improve smart systems in tech companies.
- Healthcare Sector: Analyzing medical data to improve healthcare services and develop treatment systems.
- Finance and Banking: Analyzing financial data to improve investment strategies and risk management.
- Digital Marketing: Using data to understand consumer behavior and improve marketing strategies.
- Big Data Projects: Managing and analyzing large datasets for companies and institutions.
- Academic Research: Working in universities or research centers to develop scientific research based on data analysis.
- Technology and Communications: Developing innovative technological solutions for data analysis in communications and IT companies.
- Consulting: Providing consulting services to companies to improve decisions and strategies based on data.
These fields offer diverse opportunities for graduates to utilize their data science skills, contributing to improved performance and data-driven decision-making.
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