Department objectives: 

1- Developing specialized academic programs in the field of information systems, data science and analytics to meet the needs of the labor market.

2- Enhancing future skills, competitiveness, and innovation.

3- Providing a technologically and intellectually supportive environment that enhances quality of life.

4- Achieving local and global quality standards and academic accreditation.

5- Activating academic and research activities to serve the community

Program Mission:

Preparing distinguished scientific and technical female competencies in data science and analytics by providing an integrated interactive environment for education and innovative scientific research that fosters analytical and creative skills in compliance with local and international quality standards, thus contributing to the community.

Program Objectives: 

1. Preparing female workforces specialized in data science and analytics capable of meeting labor market needs

2. Developing future skills and enhancing competitiveness and innovation in the field of data science and analytics

3. Facilitating an interactive educational environment that promotes quality of life.

4. Achieving academic accreditation and quality standards on a local and international level.

5. Promoting academic activities and supporting basic and applied research collaborations in the field of data science and analytics to contribute to the community

Program Learning Outcomes (PLOs):

Knowledge:

1. K1: Explain the main theories, concepts, processes, techniques and tools of data science and analytics and its related fields for professional practices.
2. K2: Identify appropriate research methods and investigation techniques related to current and emerging topics within the data science and analytics discipline.

Skills:

1. S1: Apply theory, techniques, and tools throughout the data science lifecycle and employ the resulting knowledge to satisfy stakeholders' needs.
2. S2: Analyze complex data science problems, leveraging principles of computing and other relevant disciplines and employ research methodologies to identify solutions.
3. S3: Design, implement, and evaluate data-driven solutions using cutting-edge technologies to meet specified requirements in the context of data science and its associated disciplines.
4. S4: Demonstrate effective communication skills in various professional contexts relevant to data science, including presenting technical information and effectively conveying insights derived from data analysis.

Values

1. V1: Recognize professional and societal responsibilities in data science and make informed judgments in computing practice based on domain-specific, legal and ethical principles.
2. V2: Function effectively as a self-reliant and cooperative member or leader within a team engaged in data science activities.

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Program Graduate Attribute (PGA): 

The graduates of the DS program will have the following attributes:

1. Analytical and Creative Problem-Solving: Demonstrate strong analytical thinking skills and creative problem-solving abilities to analyze complex data science problems and identify innovative solutions.

2. Community Service and Impact: Apply data science and analytics skills to contribute to the betterment of the community through impactful projects and initiatives that address societal challenges

3. Business Leadership: Possess the knowledge and skills to lead data-driven initiatives in businesses and organizations, effectively leveraging data science and analytics to drive success and achieve strategic goals.​

4. Value Creation: Understand the value and potential of data science and analytics in various domains and industries, and effectively utilize these skills to create value for stakeholders and optimize business outcomes.

5. Continuous Learning and Awareness: Stay informed about the latest trends, techniques, and advancements in data science and analytics, continuously expanding knowledge and adapting to the evolving landscape of the field

​6. Self-Development and Professional Growth: Demonstrate a commitment to personal and professional growth, continuously improving skills, and staying updated with emerging technologies and practices in data science and analytics. 

7. Information Efficiency: Effectively gather, analyze, and interpret data to extract meaningful insights and make informed decisions, ensuring information efficiency and accuracy throughout the data science lifecycle. 

8. Effective Communication: Possess strong communication skills to effectively convey complex technical information, insights, and findings to diverse audiences, facilitating effective communication within the team and with stakeholders..

9.​ Ethical Decision-Making: Demonstrate a strong understanding of ethical principles and apply them in data science and analytics practice, making informed and responsible decisions that consider the ethical implications of data collection, analysis, and usage.​

​​Academic plan for the bachelor stage for Data Science and Analytics Program

The study plan for the undergraduate program in Data science and Analytics at the College of Computer and Information Sciences consists of (129) study units. The study plan has been distributed over (2) semesters in the academic year distributed as follows: