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Data Science and Artificial Intelligence

  2. About
  3. Faculties
  4. Faculty of IT
  5. Data Science and Artificial Intelligence
134 Credit Hours 60% Minimum Grade

Department Welcome

Dr. Mohammad Bani Taha

“ Welcome to the Data Science and Artificial intelligence Department! ”
Dr. Mohammad Bani Taha

Founded in 2020, our department is part of the Faculty of Information Technology and is dedicated to advancing the fields of data science and AI through cutting-edge education and research. Our program provides a robust curriculum in machine learning, big data analytics, AI ethics, and data-driven decision-making, equipping students with the skills necessary to tackle complex real-world challenges.

In our department, we utilize state-of-the-art hardware and software to give students hands-on experience with the latest tools in the industry. Our faculty members, hailing from prestigious academic and research backgrounds, are actively engaged in pioneering research, enriching our curriculum with insights from the forefront of AI and data science. This integration of advanced technology and research ensures that our graduates are exceptionally prepared to excel in the fast-evolving tech landscape.

We look forward to supporting you in your journey to become innovators and leaders in data science and artificial intelligence!

Study Plan

Details about the study plan and curriculum.

Course Curriculum: 134 Credit Hours

Faculty Information Technology Faculty
Department Data Science and Artificial Intelligence
Credit Hours 134
Version 5

A. Remedial Requirements (0 Credit Hours)
Description
Students must sit for placement tests in English, Arabic, and Computer. Students who fail any of these tests are required to take the corresponding remedial course 900099, 900097, or 900096, respectively.
B. University Compulsory Course Requirements: 16 Credit Hours
Course No Course Name Credit Hours Prerequisite Learning Models (F, B, O)
0900103 Swimming 1 -- F
0900111 Military Science 3 -- O
0900119 Life Skills 1 -- F
0900120 Arabic Communication Skills (1) 3 0900097* B
0900122 Entrepreneurship and Innovation 1 -- F
0900123 Leadership and Social Responsibility 1 -- F
0900130 English Communication Skills (1) 3 0900099* B
0900131 English Communication Skills (2) 3 0900130 B
C. University Elective Course Requirements: 9 Credit Hours
1. Humanities: 3 Credit Hours
Course No Course Name Credit Hours Prerequisite Learning Models (F, B, O)
0900102 Sports 3 -- O
0900113 Interpersonal and Intercultural Communication 3 -- O
0900117 Civic Awareness 3 -- O
0900118 Cultural Development 3 -- O
0900124 Human Rights 3 -- O
0900140 Appreciation of Art 3 -- O
0900141 Appreciation of Music 3 -- O
2. Science, Technology, Agriculture, and Health: 3 Credit Hours
Course No Course Name Credit Hours Prerequisite Learning Models (F, B, O)
0900106 General Statistics 3 -- O
0900114 Civilization and Thought 3 -- O
0900115 Social Ethics 3 -- O
0900133 Research Methodology 3 -- O
0900150 Introduction to Economics 3 -- O
3. Social and Economic Sciences: 3 Credit Hours
Course No Course Name Credit Hours Prerequisite Learning Models (F, B, O)
0900116 Bio-Ethics 3 -- O
0900172 Development and Environment 3 -- O
0900171 Science and Society 3 -- O
0900180 Computer Skills 3 090096* O
0900190 Digital Culture 3 -- O
0900185 Astronomy 3 -- O

Compulsory Requirements: 21 Credit Hours
Course No Course Title Credit Hours Contact Hours Prerequisite Learning Models (F, B, O)
0401111 Discrete Structures 3 Lecture: 3
Lab: 0		 - F
0401121 Programming Fundamentals 3 Lecture: 3
Lab: 0		 *0401120 F
0401151 Introduction to Information Systems 3 Lecture: 3
Lab: 0		 - O
0900213 Technical Writing and Documentation 3 Lecture: 3
Lab: 0		 - F
0903101 Calculus (1) 3 Lecture: 3
Lab: 0		 - F
0903102 Calculus (2) 3 Lecture: 3
Lab: 0		 0903101 F
0904101 General Physics (1) 3 Lecture: 3
Lab: 0		 - F

A. Compulsory Requirements: 67 Credit Hours
Course No Course Title Credit Hours Contact Hours Prerequisite
– Co-requisite		 Learning Models (F, B, O)
0401120 Programming Fundamentals Lab 1 Lecture: 0
Lab: 3		 *0401121 F
0401122 Object Oriented Programming Language 3 Lecture: 3
Lab: 0		 0401121 + *0401123 F
0401123 Object Oriented Programming Language Lab 1 Lecture: 0
Lab: 3		 *0401122 F
0401321 Web-Based Programming and Applications 3 Lecture: 3
Lab: 0		 0401122 + *0401322 F
0401322 Web-Based Programming and Applications Lab 1 Lecture: 0
Lab: 3		 *0401321 F
0401212 Data Structures 3 Lecture: 3
Lab: 0		 0401122 F
0401251 Database Fundamentals 3 Lecture: 3
Lab: 0		 0401212 B
0401313 Principles of Computer Algorithms 3 Lecture: 3
Lab: 0		 0401212 F
0402333 Applied Data Mining 3 Lecture: 3
Lab: 0		 0401313 F
0401314 Fundamentals of Artificial Intelligence 3 Lecture: 3
Lab: 0		 0401313 F
0401332 Operating Systems Concepts 3 Lecture: 3
Lab: 0		 0401313 F
0402101 Data Science Concepts 3 Lecture: 3
Lab: 0		 0401151 B
0402112 Statistical Methods for Data Science 3 Lecture: 3
Lab: 0		 0903281 B
0402201 Data Engineering 3 Lecture: 3
Lab: 0		 0402101 F
0402251 Data Exploration and Visualization 3 Lecture: 3
Lab: 0		 0402101 B
0402221 Data Science Programming 3 Lecture: 3
Lab: 0		 0401122 + *0402222 F
0402222 Data Science Programming Lab 1 Lecture: 0
Lab: 3		 *0402221 F
0402321 Advanced Data Science Programming 3 Lecture: 3
Lab: 0		 0402221 F
0402331 Machine Learning 3 Lecture: 3
Lab: 0		 0402201 F
0402451 Big Data 3 Lecture: 3
Lab: 0		 0402201 F
0402452 Information Retrieval 3 Lecture: 3
Lab: 0		 0402331 F
0402332 Neural Networks and Deep Learning 3 Lecture: 3
Lab: 0		 0402331 F
0402441 Natural Language Processing and Text Mining 3 Lecture: 3
Lab: 0		 0402331 F
0402493 Gradation Project-1 1 Lecture: -
Lab: -		 Department Approval + Completion of 99 cr. Hrs. B
0402494 Graduation Project-2 2 Lecture: -
Lab: -		 0402493 B
0402499 Practical Training 3 Lecture: -
Lab: -		 Department Approval + Completion of 90 cr. Hrs. B
B. Electives Requirements: 9 Credit Hours
Course No Course Title Credit Hours Contact Hours Prerequisite
– Co-requisite		 Learning Models (F, B, O)
0402311 Time Series Analysis 3 Lecture: 3
Lab: 0		 0402331 F
0402421 Social Media and Behavioral Analysis 3 Lecture: 3
Lab: 0		 0402331 B
0402435 Special Topics in Data Science (1) 3 Lecture: 3
Lab: 0		 Department Approval F
0402436 Special Topics in Data Science (2) 3 Lecture: 3
Lab: 0		 Department Approval F
0402437 Special Topics in Data Science (3) 3 Lecture: 3
Lab: 0		 Department Approval B
0402432 Data Regression 3 Lecture: 3
Lab: 0		 0402331 F
0402471 Software Tools for Data Science 3 Lecture: 3
Lab: 0		 0402331 B
0402342 Pattern Recognition 3 Lecture: 3
Lab: 0		 0401313 F
0402341 Data Security 3 Lecture: 3
Lab: 0		 0401151 F
0402433 Expert Systems 3 Lecture: 3
Lab: 0		 0401314 B
0402434 Introduction to Robotics 3 Lecture: 3
Lab: 0		 0401314 F
C. Ancillary Requirements: 6 Credit Hours
Course No Course Title Credit Hours Contact Hours Prerequisite Learning Models (F, B, O)
0903281 Probability and Statistics 3 Lecture: 3
Lab: 0		 0903101 F
0402213 Linear Algebra 3 Lecture: 3
Lab: 0		 0401121 + 0903101 F

Students may choose any course(s) offered by the University in accordance with University regulations.

Additional Information

(*) denotes that the prerequisite must be taken concurrently.

Learning Models
Learning Models No. of Credit Hours %
Face to Face (F) 77 57.4%
Blended (B) 39 29.2%
Online (O) 18 13.4%

Elective Information

  • Free Electives: 3 Face to Face and 3 Blended
  • Electives Requirements: 3 Blended and 6 Face to Face

Guidance Plan

Guidelines and plan for student guidance.

Course Curriculum: 134 Credit Hours (2022-2023)

Fall: 17 credit hours.
Course Number Title Cr. Prerequisite
0401121 Programming Fundamentals 3 0401120*
0401120 Programming Fundamentals Lab 1 0401121*
0401111 Discrete Structures 3 --
0903101 Calculus (1) 3 --
0904101 General Physics (1) 3 --
0401151 Introduction to Information Systems 3 --
University Compulsory 1 --
Spring: 17 credit hours.
Course Number Title Cr. Prerequisite
0401122 Object-Oriented Programming 3 0401121
0401123 Object-Oriented Programming Lab 1 0401122*
0402101 Data Science Concepts 3 0401151
0903102 Calculus (2) 3 0903101
0900213 Technical Writing and Documentation 3 --
0900130 English Communication Skills (1) 3 0900099**
University Compulsory 1 --

Fall: 17 credit hours.
Course Number Title Cr. Prerequisite
0402201 Data Engineering 3 0402101
0401212 Data Structures 3 0401122
0402221 Data Science Programming 3 0401122
0402222 Data Science Programming Lab 1 0402221*
0900131 English Communication Skills (2) 3 0900130
0903281 Probability and Statistics 3 --
University Compulsory 1 --
Spring: 18 credit hours.
Course Number Title Cr. Prerequisite
0402251 Data Exploration and Visualization 3 0402101
0401313 Principles of Computer Algorithms 3 0401212
0402321 Advanced Data Science Programming 3 0402221
0401251 Database Fundamentals 3 0401212
0900111 Military Science 3 --
0900120 Arabic Communication Skills 3 0900097*

Fall Semester (16 credit hours)
Course Number Title Cr. Prerequisite
0402331 Machine Learning 3 0402221
0402112 Statistical Methods for Data Science 3 0903281
0402213 Linear Algebra 3 --
0401321 Web-based Programming and Applications 3 0401122
0401322 Web-based Programming and Applications Lab 1 0401321*
University Elective -- 3 --
Spring Semester (18 credit hours)
Course Number Title Cr. Prerequisite
0401332 Operating Systems Concepts 3 0401313
0402451 Big Data 3 0402201
0401314 Fundamentals of Artificial Intelligence 3 0401313
0402452 Information Retrieval 3 0402331
Department Elective -- 3 Dept. Approv.
University Elective -- 3 --

Fall Semester (16 credit hours)
Course Number Title Cr. Prerequisite
0402332 Neural Networks and Deep Learning 3 0402331
0402333 Applied Data Mining 3 0401313
0402499 Practical Training 3 Dept. Approv.
0402491 Graduation Project I 1 Dept. Approv.
Department Elective -- 3 Dept. Approv.
Free Elective -- 3 --
University Compulsory -- 1 --
Spring Semester (15 credit hours)
Course Number Title Cr. Prerequisite
0402441 Natural Language Processing and Text Mining 3 0402331
0402492 Graduation Project II 2 0402491
Department Elective -- 3 Dept. Approv.
Free Elective -- 3 --
University Elective -- 3 --
  • * Co-requisite (a course that must be taken concurrently).
  • ** Passing a placemat test.

List of Competencies

DS & AI List of Competencies

A. Knowledge and Understanding

Overview the theoretical and technical concepts related to data science and Artificial Intelligence.
Analyze a complex data science problem.
Apply principles of data science and AI to identify solutions.
Understand computing contemporary issues and devise viable solutions for them.
Understand and engage in continuing professional development.

B. Practical Skills

Apply data science principles to analyze data from different sources to produce predictive results.
Use a variety of computer programming languages to implement AI solutions for different computing problems.
Apply AI concepts and methodologies, such as Machine Learning and Deep Learning, to explore hidden patterns in massive datasets.

C. Communication Skills

Communicate effectively in a variety of professional contexts.
Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles.

D. Thinking Skills

Think out-of-the-box and be ready to participate in IT-related business ventures.
Understand and engage in continuing professional development.

Program Learning Outcomes

Data Science & Artificial Intelligence Program Learning Outcomes

Student learning outcomes describe what students are expected to know and be able to do by the time of graduation. By the time of graduation, the Data Science Department's Bachelor of Science program must enable students to attain an ability to:

Apply data science theory and software development fundamentals to produce AI-based solutions.
Determine an algorithm’s efficiency, computability, and resource usage.
Utilize the latest tools and technologies in data science and AI to develop creative and innovative solutions.
Function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline.
Conduct scientific research and practical projects that produce significant AI software solutions.

Course Description

Detailed descriptions of the courses offered.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402101 Data Science Concepts 3 CH 0401151 - 3 + 0
This course is the starting point for students to learn about the data science roadmap, main principles, and techniques. Students will study typical tasks of data science, including data collection, exploration, feature extraction, descriptive and predictive analysis, and performance measurement. Real-world applications will be presented to emphasize the impact of these concepts.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402112 Statistical Methods for Data Science 3 CH 0903281 - 3 + 0
This course emphasizes applied statistics within data science, covering estimates, categorical data exploration, data distributions, statistical inferences, and significance testing. Practical applications are incorporated using R and/or Python programming languages.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
04022201 Data Engineering 3 CH 0402101 - 3 + 0
This course introduces data engineering in data science, focusing on data lifecycle management and ETL/ELT processes, data formats, and engineering tools. Students will practice collecting and pre-processing data for data science applications.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402213 Linear Algebra 3 CH - 402101 3 + 0
This course discusses Linear Algebra for data science, covering vectors, matrices, matrix-vector equations, systems of linear equations, Euclidean vector spaces, eigenvalue/eigenvector analysis, and principal component analysis. A programming language will be used for analysis tasks.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402251 Data Exploration and Visualization 3 CH 0402101 - 3 + 0
This course introduces data exploration and visualization principles. Topics include design, data mapping, positioning, color scales, and storytelling. Students will develop visualizations, explore datasets, and create dashboards to communicate insights.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402221 Data Science Programming 3 CH 0401122 0402222 3 + 0
This course provides a hands-on introduction to Python programming, covering problem-solving, data types, loops, lists, functions, dictionaries, sets, regular expressions, I/O files, JSON files, and object-oriented design.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402222 Data Science Programming Lab 1 CH - 0402221 0 + 3
This course highlights applied statistics in data science, covering statistical estimates, categorical data exploration, correlation measures, data distributions, statistical inferences, experiments, and significance testing. Practical applications are incorporated using R and/or Python.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402321 Advanced Data Science Programming 3 CH 0402221 - 3 + 0
This course explores advanced Python programming, including GUI, network programming, and databases. Students will design, develop, and solve real-life projects, covering TCP/IP programming and MySQL, with a focus on research, practical, and presentation skills.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402331 Machine Learning 3 CH 0402201 - 3 + 0
This course covers machine learning algorithms, including decision trees, statistical methods, supervised, unsupervised, and reinforcement learning. It also explores concepts like inductive bias, PAC learning, and Occam’s Razor, with hands-on experiments.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402451 Big Data 3 CH 0402201 - 3 + 0
This course introduces Big Data platforms, including Hadoop, Spark, and data storage methods like HDFS, HBase, and Hive. Students will learn data distribution, processing, analytics algorithms, and visualization challenges for handling large, complex datasets.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402452 Information Retrieval 3 CH 0402331 - 3 + 0
This course covers Information Retrieval systems, focusing on text-based search, indexing, document clustering, and classification. Students will explore IR techniques for retrieving relevant text, images, or video based on user queries.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402332 Neural Networks and Deep Learning 3 CH 0402331 - 3 + 0
This course covers foundational concepts of neural networks and deep learning, including training and applying neural networks, CNNs, RNNs, and reinforcement learning, with a focus on mathematical foundations for image processing and forecasting.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402441 Natural Language Processing and Text Mining 3 CH 0402331 - 3 + 0
This course covers text mining and NLP, including document classification, entity tagging, information extraction, and machine translation, with hands-on practice using libraries like scikit-learn and TensorFlow.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402311 Time Series Analysis 3 CH 0402331 - 3 + 0
This introductory course covers time series analysis techniques, including ARMA/ARIMA models, spectral analysis, and multivariate time series, preparing students to apply forecasting techniques.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402421 Social Media and Behavioral Analysis 3 CH 0402331 - 3 + 0
This course introduces social network analysis, covering graph theory, network community detection, information propagation, and other topics, focusing on the analysis of large-scale network data.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402435 Special Topics in Data Science I 3 CH Department Approval - 3 + 0
This course covers evolving Data Science and AI topics selected by the department, promoting research and supporting the study plan.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402436 Special Topics in Data Science II 3 CH Department Approval - 3 + 0
Topics will be assigned by the department on evolving Data science and AI techniques and related topics to support the study plan and to encourage further research by students.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402437 Special Topics in Data Science III 3 CH Department Approval - 3 + 0
Topics will be assigned by the department on evolving Data science and AI techniques and related topics to support the study plan and to encourage further research by students.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402432 Data Regression 3 CH 0402331 - 3 + 0
This course introduces students to data regression, the most widely used statistical technique. It estimates relationships between independent variables (predictors) and a dependent variable (outcome), covering regression analysis, least squares, and inference using regression models.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402471 Software Tools for Data Science 3 CH 0402331 - 3 + 0
This course introduces students to various software tools used to collect and analyze data, such as Beautiful Soup and pandas libraries, with hands-on practice in building machine learning models.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402351 Data Modeling and Simulation 3 CH 0401212 - 3 + 0
This course provides an introduction to modeling and simulation, covering both theoretical and applied aspects, including discrete-event simulation, model quality, and input/output analysis.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402341 Data Security 3 CH 0401151 - 3 + 0
This course covers security and privacy concepts in data science and AI applications, exploring cybersecurity risks and mitigation techniques.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402342 Pattern Recognition 3 CH 0401313 - 3 + 0
This course examines statistical pattern recognition approaches, technologies, and algorithms, including feature extraction and neural networks.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402433 Expert Systems 3 CH 0401314 - 3 + 0
This course enables students to solve problems using explicit knowledge and reasoning techniques and develop expert systems for simple problems.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402434 Introduction to Robotics 3 CH 0401314 - 3 + 0
This course provides an introduction to robotics, focusing on fundamental components and practical experience in designing and constructing robots.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402491 Graduation Project (1) 1 CH Department Approval + completion of 99 Cr. Hrs. - 1 + 0
The graduation project provides an opportunity for students to employ their skills, targeting software production and documentation, with planning guided by an advisor.

Course no Title Credit Hours Prerequisite Co-requisite Distribution
0402492 Graduation Project (2) 2 CH 0402491 - 2 + 0
Graduation Project (2) continues the work of the first part, including implementation, software testing, and documentation that follows professional guidelines.