Al-Ahliyya Amman University
Program Description
Data Science and Artificial Intelligence
Bachelor
The Artificial Intelligence Department was established in 2020 with the aim of providing local and regional labor markets with distinguished graduates who possess scientific knowledge and practical experience in artificial intelligence. The department aligns with the vision of the College of Information Technology, which seeks to provide excellent education in an innovative learning environment that keeps up with the latest developments. It equips students with technical knowledge and leadership skills that meet labor market needs and keep pace with ongoing changes in the field.
Students earn a Bachelor’s degree in Artificial Intelligence after successfully completing all required and elective coursework, totaling 132 credit hours. The program is designed to meet international academic standards and to satisfy the growing local, regional, and global demand for qualified professionals in the field. It emphasizes a strong foundation in AI fundamentals, machine learning, and hands-on practical training.
The Artificial Intelligence program focuses on providing a blend of theoretical knowledge and practical skills through carefully chosen core courses that serve as a strong foundation for students. The specialized courses include Introduction to Artificial Intelligence, Machine Learning, Deep Learning, Applied Artificial Intelligence, Robotics, Computer Vision, Natural Language Processing, Artificial Intelligence Algorithms, Data Analysis, AI in Games, Graduation Project, and Practical Training.
These courses are supported by practical labs that enable students to apply their knowledge in real-world scenarios. Community service is also an integral requirement of the program; students must complete 10 hours of community service as part of their graduation criteria, fostering social responsibility and contributing to sustainable development.
Upon graduation, students are not only equipped with academic knowledge but also with practical competencies that support the College’s goals of excellence in education and training, align with market needs, and contribute to sustainable development through active community engagement and technological innovation.
Data Science and Artificial Intelligence
Number Of Credit Hours
132
Faculty of Information Technology
Admission Requirements
Admission requirements of the Data Science and Artificial Intelligence program include a High School Certificate or equivalent in the following:
60%
- Scientific
- Scientific - Medical Field
- Scientific - Engineering Field
- Scientific - Pure Sciences Field
- Comprehensive Health Education
- Informatics Administration
- Industrial
- Household Economy
- Agricultural
Job Opportunities
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Machine Learning Engineer
o Design, develop, and implement machine learning algorithms and models to solve specific problems. Work with large datasets and build systems capable of learning and making decisions based on data.
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Deep Learning Engineer
o Specialize in creating neural networks and deep learning models to solve complex problems in areas such as image recognition, natural language processing, and autonomous systems.
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Data Analyst
o Analyze datasets to identify patterns, trends, and relationships. Provide actionable insights to improve business processes, often focusing on data visualization and presenting findings to decision-makers.
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Natural Language Processing (NLP) Engineer
o Develop systems that enable computers to understand, interpret, and generate human language. Work on tasks like speech recognition, chatbots, and text analysis.
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Computer Vision Engineer
o Create algorithms and models that enable computers to interpret and understand visual data from the world, such as image recognition, object detection, and video analysis.
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Data Engineer
o Design and build systems and infrastructure that allow data scientists and analysts to access and analyze data. Focus on data collection, transformation, and storage.
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AI Software Engineer
o Develop and implement AI-driven software solutions. Work on integrating machine learning models into products and services to enable them to adapt and improve over time.
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Business Intelligence Analyst
o Analyze business data and use AI and machine learning techniques to provide actionable insights that help organizations make data-driven decisions.
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AI Product Manager
o Manage the development and deployment of AI-powered products. Work closely with engineering teams to translate business needs into AI solutions and ensure that products meet customer requirements.
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Robotics Engineer
· Work on developing intelligent robotic systems that can perform tasks autonomously. Integrate AI and machine learning with robotics to create systems for industries like manufacturing, healthcare, and logistics.
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AI Solutions Architect
· Design and implement AI infrastructure and solutions for companies. This role requires understanding both technical and business aspects to ensure seamless integration of AI technologies with existing systems.
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AI Ethics Specialist
· Work on the ethical aspects of AI technologies, ensuring that intelligent systems are designed and implemented responsibly. Address issues like bias, fairness, privacy, and transparency in AI systems.
Study Plans and Program Files
Educational Objectives
Program Educational Objectives (PEO's):
- PEO-1. Professional Success: Graduates will succeed in the field of data science and artificial intelligence by applying AI techniques, machine learning, and data analysis to develop innovative solutions that meet the growing needs of the labor market.
- PEO-2. Continuous Professional Development: Graduates will demonstrate ongoing professional growth by engaging in further education, earning specialized certifications in emerging fields such as machine learning, big data, and artificial intelligence.
- PEO-3. Innovative Contributions: Graduates will contribute to the development of innovative solutions using AI and data analysis to address societal and industrial challenges, promoting sustainable technological advancement.
- PEO-4. Effective Communication and Leadership: Graduates will acquire leadership and communication skills that enable them to work within multidisciplinary teams and lead projects utilizing data science and AI techniques to meet the needs of industry and society.
Mapping between the Program Mission and PEOs
|
PEO |
Key Points in the Mission |
Mapping between Mission and PEO |
|
PEO-1: Professional Success |
"To provide distinguished education in a creative environment that keeps up with the latest developments in the field of data science and artificial intelligence." |
The mission focuses on equipping students with technical knowledge in AI and data analysis, enabling them to succeed in fields like data science and AI and contribute to innovative solutions in the labor market. |
|
PEO-2: Continuous Professional Development |
"Equipping students with technical knowledge and leadership skills that meet the needs of the labor market." |
The mission emphasizes continuous learning and professional growth, preparing graduates to stay updated with technological advancements in AI and data science. |
|
PEO-3: Innovative Contributions |
"Activating scientific research and enhancing collaboration with the local community and industry to provide innovative technological solutions." |
The mission emphasizes scientific research and collaboration with industry to provide innovative solutions in AI and data analysis, contributing to sustainable community development. |
|
PEO-4: Effective Communication and Leadership |
"Equipping students with leadership skills and technical knowledge that meet the needs of the labor market." |
The mission highlights the importance of leadership and effective communication within multidisciplinary teams, enabling graduates to lead AI and data-driven projects and address industry and societal needs. |
Students Outcomes (SO's):
- SO-1: Analyze a complex computing problem and to apply principles of computing and data science and artificial intelligence and other relevant disciplines to identify solutions.
- SO-2: Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program’s discipline.
- SO-3: Communicate effectively in a variety of professional contexts.
- SO-4: Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles.
- SO-5: Function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline.
- SO-6: Understand and apply theories, and tools thorough the data science lifecycle and employ the resulting knowledge to satisfy stockholder's need.
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Educational Objectives with Student Outcomes:
| PEO-1 | PEO-2 | PEO-3 | PEO-4 | |
| SO-1 | √ | |||
| SO-2 | √ | |||
| SO-3 | √ | √ | ||
| SO-4 | √ | |||
| SO-5 | √ | √ | ||
| SO-6 | √ | √ |
