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