College of Computing and Informatics

College of Computing and Informatics

Introduction

The College of Computing and Informatics offers Bachelor of Science in Data Science program that aims to enhances and contributes to the National strategic plans for the data scientists needs in order to localizing job market demands. 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 labor market is still suffering from a severe shortage of qualified data scientists. Thus, this program is introduced to fill in the gap by graduating highly qualified data scientists, who can make use of the latest artificial intelligence techniques to analyze data and extract knowledge.

- Therefore, the College of Computing and Informatics in the Saudi Electronic University presenting an integrated program for the Bachelor of Data Science, that was implemented based on international standards and conform with the latest techniques and methods.

Program Objectives

1. Development of a technically proficient workforce comprising of Saudi citizens capable of carrying out software development projects to the best of international standards.

2. Developing both academic and professional skills in the domain of data science and AI.

3. Enhancing students' experience by enabling them to solve academic and practical problems in their areas of specialization.

4. Implementing best practices to develop comprehensive data analysis projects plans.

5. Preparing students to meet the labor market requirements in data science domains.

6. Integrating the academic programs by bridging the gap between theoretical advances and practical applications.

Duration of Study in the Program

8 semesters.

Program Learning Outcomes

1. Recognize the concepts of computing and mathematics related to the discipline.

2. Master the current techniques, skills, and tools necessary for the computing practice.

3. Demonstrate algorithmic, computational, and statistical models in data science.

4. Comprehend the local and global impact of computing on individuals, organizations, and the society.

5. Analyze a problem, identify and define the computing requirements appropriate to its solution.

6. Apply mathematical foundations, algorithmic principles, and Data science theories in modeling.

7. Implement theories and principles using cutting edge technologies in the analysis, design, implementation and testing of computer-based systems.

8. Construct machine learning and AI optimization models using problem-solving strategies for data analytics.

9. Function effectively on teamwork activities to accomplish a common goal.

10. Identify the needs for continuous development of professional skills with the ability to engage all group members.

11. Develop projects to visualize data for exploration, analysis, and communication.

12. Communicate effectively with a range of audiences, both orally and in a written form, using appropriate media.

Career Opportunities for Graduates of the Program

Data Administrator.

Computer Systems Analyst.

Data Scientist.

Software Developer.

Data Analyst.

Big Data Analyst.

Financial Data Analyst.

Machine Learning Engineer.

Business Intelligence Analyst.

Big Data Administrator.

Data Mining Analyst.

Big Data Architect.

Data Visualization Developer.

University Requirements are 34 credits
Course Code ​ Course Name​ Credit Hours Prerequisites
CS001 Computer Essentials 3 -
ENG001 English Language Skills 8 -
CI001 Academic Skills 2 -
MATH001 Fundamentals of Mathematics 3 -
ENG002 English Language Skills 2 8 -
COMM001 Communication Skills 2 -
ISLM101 Islamic Culture 1 2 Passing the First Year
ISLM102 Islamic Culture 2 2 -
ISLM103 Islamic Culture 3 2 -
ISLM104 Islamic Culture 4 2 -
Total 34
College requirements: 24 Credits
Course Code ​ Course Name​ Credit Hours Prerequisites
DS230 Object Oriented Programming 3 Passing the First Year
ENG103 Technical Writing 3 Passing the First Year
MATH150 Discrete Mathematics 3 Passing the First Year
DS240 Data Structure 3 DS230
MATH151 Linear Algebra 3 MATH150
DS350 Introduction to Database 3 DS240
DS351 Operating Systems 3 DS243
DS360 Computer Networks 3 DS243
CS499 Practical Training Pass/Fail Passing 86 Credit Hours
Total 24
Specialization requirements: 72 Credits
Course Code ​ Course Name​ Credit Hours Prerequisites
SCI 101 General Physics 1 3 Passing the First Year
DS231 Introduction to Data Science Programming 3 Passing the First Year
DS241 Calculus 3 MATH150
DS242 Advanced Data Science Programming 3 DS231
DS243 Computer Architecture and Organization 3 -
SCI 201 General Physics 2 3 SCI 101
STAT202 Introduction to Statistics and Probabilities 3 MATH150
DS352 Design and Analysis of Algorithms 3 DS240
DS353 Project Management in Computing 3 -
DS361 System Analysis and Design 3 DS240
DS362 Web Programming 3 DS350
DS363 Artificial Intelligence 3 DS352
DS388 Data Curation (Management and Organization) 3 DS320
DS364 Data Curation (Management and Organization) 3 DS350
DS471 Machine Learning 3 DS363
DS472 Data Mining 3 DS364
DS479 Senior Project 1 3 DS361, DS362
DS4xx Elective 1 3 -
DS4xx Elective 2 3 -
DS480 Data Visualization 3 DS472
DS481 Professional Ethics in Data Science 3 -
DS489 Senior Project 2 3 DS479
DS4xx Elective 3 3 -
DS4xx Elective 4 3 -
Total 72
Track 1 Courses – Artificial Intelligence
Course Code ​ Course Name​ Credit Hours Prerequisites
DS473 Computer Vision 3 DS363
DS474 Decision Support Systems 3 S363
DS482 Deep Learning 3 DS471
DS483 Natural Language Processing 3 DS471
Total
Track 2 Courses – Big Data Analytics
Course Code ​ Course Name​ Credit Hours Prerequisites
DS475 Big Data Modelling 3 DS363
DS476 Big Data Integration and Processing 3 DS363
DS484 Big Data Optimization 3 DS475
DS485 Business Intelligence 3 DS475
Total
Level One
Course Code ​ Course Name​ Credit Hours Prerequisites
CS001 Computer Essentials 3 -
ENG001 English Language Skills 8 -
CI001 Academic Skills 2 -
Total 13
Level Two
Course Code ​ Course Name​ Credit Hours Prerequisites
MATH001 Fundamentals of Mathematics 3 -
ENG002 English Language Skills 2 8 -
COMM001 Communication Skills 2 -
Total 13
Level Three
Course Code ​ Course Name​ Credit Hours Prerequisites
SCI 101 General Physics 1 3 Passing the First Year
DS140 Object Oriented Programming 3 Passing the First Year
ENG103 Technical Writing 3 Passing the First Year
MATH150 Discrete Mathematics 3 Passing the First Year
DS240 Introduction to Data Science Programming 3 Passing the First Year
ISLM101 ISLM101 2 Passing the First Year
Total 17
Level Four
Course Code ​ Course Name​ Credit Hours Prerequisites
MATH151 Linear Algebra 3 MATH150
DS240 Data Structure 3 DS140
DS241 Calculus 3 MATH150
DS242 Advanced Data Science Programming 3 DS240
DS243 Computer Architecture and Organization 3 -
ISLM102 ISLM102 2 -
Total 17
Level Five
Course Code ​ Course Name​ Credit Hours Prerequisites
SCI 201 General Physics 2 3 SCI 101
DS350 Introduction to Database 3 DS240
DS351 Operating Systems 3 DS243
STAT202 Introduction to Statistics and Probabilities 3 MATH150
DS352 Design and Analysis of Algorithms 3 DS240
DS353 Project Management in Computing 3 -
Total 18
Level Six
Course Code ​ Course Name​ Credit Hours Prerequisites
DS360 Computer Networks 3 DS243
DS361 System Analysis and Design 3 DS240
DS362 Web Programming 3 DS350
DS363 Artificial Intelligence 3 DS352
DS364 Data Curation (Management and Organization) 3 DS350
ISLM103 ISLM103 2 -
Total 17
Summer Semester (practical training)
Course Code ​ Course Name​ Credit Hours Prerequisites
DS499 Practical Training - Passing 86 Credit Hours
Total
Level Seven
Course Code ​ Course Name​ Credit Hours Prerequisites
DS470 Data Security and Privacy 3 DS364
DS471 Machine Learning 3 DS363
DS472 Data Mining 3 DS364
DS479 Senior Project 1 3 DS361, DS362
DS4xx Elective 1 3 -
DS4xx Elective 2 3 -
Total 17
Level Eight
Course Code ​ Course Name​ Credit Hours Prerequisites
ISLM104 ISLM104 2 -
DS480 Data Visualization 3 DS472
DS481 Professional Ethics in Data Science 3 -
DS489 Senior Project 2 3 DS479
DS4xx Elective 3 3 -
DS4xx Elective 4 3 -
Total 17
For study plan files

Study Plan for Bachelor of Data Science Program 2021 Click here

Study Plan for Bachelor of Data Science Program 2022 Click here