Program Description
The Bachelor of Science in Data Science and Artificial Intelligence (B.Sc. DSAI) is a four-year program which provides students with the applied knowledge and skills needed for exciting careers in the field of Data Science and Artificial Intelligence (DSAI). The program includes foundational information technology (IT) courses which, in combination with DSAI courses, will enable graduates to both understand and contribute to the IT context in which data science and artificial intelligence (AI) associated functions are performed. Students develop skills to leverage AI in the collection, analysis and interpretation of data for decision making that can be applied in any field. This is supported by data science techniques offering students a solid understanding of data management strategies. These skill sets, when consolidated through the completion of an industry work placement and a capstone project, prepare graduates for an exciting career in contemporary information technology, data science and AI.
Program Duration:
4 years
Admission Requirements:
1. High school graduation certificate or equivalent approved by the Ministry of Education and Higher Education with a minimum average of 60%, plus two courses: one final year Mathematics, and one final year Science (Biology, Physics, Chemistry) or Technology (Algorithms, Programming, Network, Computer Science, or equivalent); OR
2. Two-year Information Technology Diploma or equivalent approved by the Ministry of Education and Higher Education.
2. Two-year Information Technology Diploma or equivalent approved by the Ministry of Education and Higher Education.
1. The required score on the University Math Test or a passing score from another approved internationally recognized English language test, as validated by the Admissions & Registration Directorate; OR
2. A valid (within two years) IELTS Academic Test Report Form with an overall band of 5.0 with no individual band score (reading, writing, speaking, and listening) below 5.0; OR
3. Successful completion of Foundation Program requirements.
2. A valid (within two years) IELTS Academic Test Report Form with an overall band of 5.0 with no individual band score (reading, writing, speaking, and listening) below 5.0; OR
3. Successful completion of Foundation Program requirements.
1. Must achieve the required score on the University Math Placement Test; OR
2. A valid SAT Report Form with minimum score of 480.
2. A valid SAT Report Form with minimum score of 480.
1. Admission is competitive. Eligible applicants are ranked based on their overall final year (Grade 12 or equivalent) high school percentage, placement tests rankings, and admission priority category.
2025-2026 Study Plan:
COURSE NUMBER |
COURSE TITLE | REQUISITE | HOURS/WEEK | |||
---|---|---|---|---|---|---|
Pre-req | CO-req | CR | LEC | LAB | ||
SEMESTER 1 | ||||||
COMM1010 | English Communication I | - | - | 3 | 3 | 0 |
INFS1101 | Introduction to Computing & Problem Solving | - | - | 3 | 2 | 3 |
MATH1030 | Calculus I | MATH1020 OR AMPII Score of 85% | - | 3 | 3 | 0 |
Elective - Effective & Experiential Learning: select 1 of 3 | ||||||
EFFL1001 | Effective Learning | - | - | 3 | 3 | 0 |
EFFL1002 | Applied & Experiential Learning | - | - | 3 | 3 | 0 |
EFFL1003 | Experiential Learning & Entrepreneurship | - | - | 3 | 3 | 0 |
Semester 1 Total: | 12 | 11 | 3 | |||
SEMESTER 2 | ||||||
COMM1020 | English Communication II | COMM1010 | - | 3 | 3 | 0 |
INFS1201 | Computer Programming | INFS1101 | - | 4 | 3 | 3 |
DACS2101 | Discrete Structures | - | - | 3 | 2 | 3 |
MATH1040 | Statistics | - | - | 3 | 3 | 1 |
Semester 2 Total: | 13 | 11 | 7 | |||
SEMESTER 3 | ||||||
INFS1301 | Computing Ethics & Society | - | - | 3 | 3 | 0 |
Elective: select 1 of 2 | ||||||
SCIE1001 | Science & Its Applications | - | - | 3 | 3 | 0 |
SCIE1002 | Science & the Environment | - | - | 3 | 3 | 0 |
Semester 3 Total: | 6 | 6 | 0 | |||
Year 1 Total: | 31 | 28 | 10 |
COURSE NUMBER |
COURSE TITLE | REQUISITE | HOURS/WEEK | |||
---|---|---|---|---|---|---|
Pre-req | CO-req | CR | LEC | LAB | ||
SEMESTER 4 | ||||||
DSAI2201 | Introduction to Data Science & AI | - | - | 3 | 2 | 3 |
INFT2101 | Networking I | INFT1201 or INFS1101 | - | 4 | 3 | 3 |
DACS2202 | Introduction to Computing Systems | DACS2101 or INFT2102 AND INFS1201 | - | 4 | 3 | 3 |
MATH1050 | Linear Algebra | - | - | 3 | 3 | 1 |
Semester 4 Total: | 14 | 11 | 10 | |||
SEMESTER 5 | ||||||
DACS2201 | Introduction to Data & Cyber Security | INFT2101 | - | 3 | 2 | 3 |
DSAI3201 | Machine Learning | MATH1030 & MATH1050 & INFS3102 | - | 3 | 2 | 3 |
INFS2201 | Database Management Systems | INFS1201 | - | 3 | 2 | 3 |
INFS3102 | Object Oriented Programming | INFS1201 | - | 3 | 2 | 3 |
Semester 5 Total: | 12 | 8 | 12 | |||
SEMESTER 6 | ||||||
SOFT2301 | Software Project Management | Min 50 Credits | - | 3 | 2 | 3 |
Elective - Social Sciences, Humanities, & the Arts: select 1 of 6 | ||||||
SSHA1001 | Islamic & Arab Civilization | - | - | 3 | 3 | 0 |
SSHA1002 | Introduction to Sociology | - | - | 3 | 3 | 0 |
SSHA1003 | Introductory Psychology | - | - | 3 | 3 | 0 |
SSHA1004 | Ethical Reasoning | - | - | 3 | 3 | 0 |
SSHA1005 | Law & Society | - | - | 3 | 3 | 0 |
SSHA1006 | Introduction to the Arts | - | - | 3 | 3 | 0 |
Semester 6 Total: | 6 | 5 | 3 | |||
Year 2 Total: | 32 | 24 | 25 |
COURSE NUMBER |
COURSE TITLE | REQUISITE | HOURS/WEEK | |||
---|---|---|---|---|---|---|
Pre-req | CO-req | CR | LEC | LAB | ||
SEMESTER 7 | ||||||
DSAI4101 | Applied Deep Learning & Neural Network | DSAI3201 | - | 3 | 2 | 3 |
INFS3104 | Data Structures & Algorithms | INFS3102 & DACS2101 OR INFS3102 & INFT2102 | - | 3 | 2 | 3 |
DSAI3203 | Fundamentals of AI | DACS2101 | - | 3 | 2 | 3 |
Elective - Global Awareness & Regional Challenges: select 1 of 4 | ||||||
ECON1001 | Global Economic Concepts | - | - | 3 | 3 | 0 |
GARC1001 | Qatar History & Society | - | - | 3 | 3 | 0 |
GARC2001 | Human Development in Qatar | COMM1020 | - | 3 | 3 | 0 |
GARC2002 | Globalization & Environment | - | - | 3 | 3 | 0 |
Semester 7 Total: | 12 | 9 | 9 | |||
SEMESTER 8 | ||||||
DSAI3301 | Data Analysis & Visualization | DSAI2201 & MATH1040 | - | 3 | 2 | 3 |
DSAI3202 | Cloud Computing for DSAI | INFS3104 AND DACS2202 | - | 3 | 2 | 3 |
DSAI4104 | Fundamentals of IoT | INFT2101 | - | 3 | 2 | 3 |
DSAI3205 | Web Mining | INFS2201 & DSAI3201 | - | 3 | 2 | 3 |
Semester 8 Total: | 12 | 8 | 12 | |||
SEMESTER 9 | ||||||
DSAI3302 | Ethical AI & Data Governance | DSAI3201 AND INFS1301 | - | 3 | 2 | 3 |
Elective - Global Awareness & Regional Challenges: select 1 of 4 | ||||||
ECON1001 | Global Economic Concepts | - | - | 3 | 3 | 0 |
GARC1001 | Qatar History & Society | - | - | 3 | 3 | 0 |
GARC2001 | Human Development in Qatar | COMM1020 | - | 3 | 3 | 0 |
GARC2002 | Globalization & Environment | - | - | 3 | 3 | 0 |
Semester 9 Total: | 6 | 5 | 3 | |||
Year 3 Total: | 30 | 22 | 24 |
COURSE NUMBER |
COURSE TITLE | REQUISITE | HOURS/WEEK | |||
---|---|---|---|---|---|---|
Pre-req | CO-req | CR | LEC | LAB | ||
SEMESTER 10 | ||||||
COMP4101 | Practicum | Min 80 Credits | - | 3 | 1 | 6 |
DSAI4103 | Business Analytics | MATH1040 & DSAI3301 | - | 3 | 2 | 3 |
DSAI4105 | Natural Language Processing | DSAI4101 & INFS3104 | - | 3 | 2 | 3 |
Elective: select 1 of 2 | ||||||
DSAI4107 | Reinforcement Learning | DSAI4101 | - | 3 | 2 | 3 |
DSAI4108 | Singal And Image Processing | DSAI4101 | - | 3 | 3 | 2 |
Semester 10 Total: | 12 | 8 | 14 | |||
SEMESTER 11 | ||||||
COMP4201 | Capstone Project | COMP4101 | - | 3 | 0 | 0 |
DSAI4206 | Data-Intensive Computing | DSAI3202 | - | 3 | 2 | 3 |
Elective: select 2 of 4 | ||||||
DSAI4201 | Selected Topics in Data Science | DSAI4101 | - | 3 | 2 | 3 |
DSAI4202 | Information Retrieval | DSAI3201 | - | 3 | 2 | 3 |
DSAI4203 | Natural Language Processing with Deep Learning | DSAI4105 | - | 3 | 2 | 3 |
DSAI4204 | Computer Vision | DSAI4108 | - | 3 | 2 | 3 |
Semester 11 Total: | 12 | 6 | 9 | |||
SEMESTER 12 | ||||||
COMP4301 | Work Placement | COMP4201 ; CGPA>2.0 | - | 9 | 0 | 0 |
Semester 12 Total: | 9 | 0 | 0 | |||
Year 4 Total: | 33 | 14 | 23 | |||
Program Total | 126 | 88 | 82 |
Graduate Future Pathways:
Graduates of the Bachelor of Science in Data Science and Artificial Intelligence (B.Sc. DSAI) program may choose to further specialize or pursue graduate studies in their area.
Graduate Career Opportunities:
The Bachelor of Science in Data Science and Artificial Intelligence (B.Sc. DSAI) is an applied program with learning outcomes closely linked to the labor market. A wide range of career opportunities in the field currently exist, and include, but are not limited to, the following:
- Data Mining Analyst
- AI Architect • Business Analyst
- Big Data Specialist
- AI System Designer
- Machine Learning Specialist
- Business Intelligence Developer
- Data Scientist
- Data Science Trainer