Bachelor of Science in Data Science and Artificial Intelligence (B.Sc. DSAI)

AI3

Program Description:

AI2

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 capstone project, prepare graduates for an exciting career in contemporary information technology, data science and AI.

Program Duration:

Four 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;

OR

3. One-year Advanced Information Technology Diploma from CNA-Q, or equivalent.
 

1. The required score on the University English Placement 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.
 

1. Must achieve the required score on the University Math Placement Test;

OR

2. A valid SAT Report Form with minimum score of 480;

OR

3. Successful completion of Foundation Program Requirements. 

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.

Program Educational Objectives:

Program Educational Objectives (PEOs) describe the knowledge, skills, and competencies a graduate can demonstrate within 2-3 years of graduation.

Within a few years of graduation from the Bachelor of Science in Data Science and Artificial Intelligence (B.Sc. DSAI) program, graduates will be able to:

PEO01. Manage information technology, data-driven environments and autonomous intelligent systems

PEO02. Develop policies and procedures for approval by executive officials to ensure adherence to best practice in information technology, data management and governance, including data security and privacy aspects

PEO03. Evaluate current and emerging data collection and analysis tools to optimize business processes and fuel data-driven decisions to ensure businesses sustainability and growth

PEO04. Design digital transformation processes and systems that transform businesses and society and shape the future for the better by adhering to strict ethical principles

PEO05. Engage in lifelong learning, professional development and ethical practices

Student Learning Outcomes:

Student Learning Outcomes (SLOs) describe the knowledge, skills, and competencies a graduate can demonstrate immediately upon graduation.

Upon successful completion of the Bachelor of Science in Data Science and Artificial Intelligence (B.Sc. DSAI) program, graduates will be prepared to:

SLO01. Analyze a complex computing problem and apply principles of computing and other relevant disciplines to identify solutions

SLO02. Develop, implement, and evaluate computing- based solutions to meet requirements in the context of the program’s discipline

SLO03. Communicate effectively in a variety of professional contexts, in particular present effectively and visually results of data analytics

SLO04. Demonstrate professional responsibilities and make informed judgments in computing practice based on legal and ethical principles

SLO05. Function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline

SLO06. Apply theory, techniques, and tools throughout the data science lifecycle and employ the resulting knowledge to satisfy stakeholders’ needs

To see the 2022-2023 Study Plan pages, please CLICK HERE!

 

To see the 2023-2024 Study Plan pages, please CLICK HERE!

2024-2025 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
Effective & Experiential Learning Elective: Select 1 of 2      

EFFL1001

Effective Learning

 - - 3 3 0
EFFL1002 Applied & Experiential Learning - - 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
INFT1201 Computer Hardware -   4 3 3
MATH1040 Statistics - - 3 3 1
Semester 2 Total: 14 12 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: 32 29 10
COURSE
NUMBER		 COURSE TITLE requisite HOURS/WEEK
PRE-req CO-req CR LEC LAB
SEMESTER 4
DACS2101 Discrete Structures INFS1101 - 3 2

3
INFS2101 Web Technologies I INFS1201 - 3 2 3
INFT2101 Networking I INFT1201 OR Min 16 Credits - 4 3 3
MATH1050 Linear Algebra - - 3 3 1
Semester 4 Total: 13 10 10
SEMESTER 5
DACS2201 Introduction to Data and Cyber Security INFT2101 - 3 2 3
DSAI2201 Introduction to Data Science & AI INFS1201 - 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
Social Sciences, Humanities & the Arts Elective – 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: 31 23 25
COURSE
NUMBER		 COURSE TITLE requisite HOURS/WEEK
PRE-req co-req CR LEC LAB
SEMESTER 7
INFT2201 Introduction to Operating Systems 

INFS1201 (INFT1201 OR SOFT2301)

 - 3 2 3
INFS3104 Data Structures & Algorithms

(INFS3102 & DACS2101)
OR
(INFS3102 & INFT2102)

 - 3 2 3
INFS3201 Web Technologies II INFS2101  INFS2201  INFS3102 - 3 2 3
Global Awareness & Regional Challenges Elective: Select 1 of 4      
ECON1001 Global Economic Concepts - - 3 3 0
GARC1001 Qatar History & Society - - 3 3 0
GARC2001 Human Development in Qatar - - 3 3 0
GARC2002 Globalization & Environment - - 3 3 0
Semester 7 Total: 12 9 9
SEMESTER 8
DSAI3201 Machine Learning INFS3102
MATH1030
MATH1050		 - 3 2 3
DSAI3202 Parallel & Distributed Computing INFS3104 - 3 2 3
DSAI3203 Fundamentals of AI DACS2101 - 3 2 3
DSAI3204 IoT Application Development INFS3201 - 3 2 3
Semester 8 Total: 12 8 12
SEMESTER 9
DSAI3301 Data Analysis & Visualization DSAI2201
MATH1040		 - 3 2 3
Global Awareness & Regional Challenges Elective: Select 1 of 4      
ECON1001 Global Economic Concepts - - 3 3 0
GARC1001 Qatar History & Society - - 3 3 0
GARC2001 Human Development in Qatar - - 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
DSAI4101 Applied Deep Learning & Neural Network DSAI3201 - 3 2

3
DSAI4104 Fundamentals of IoT INFT2101 - 3 2 3
Elective: Select 1 of 2          
DSAI4102 Applied Data Mining

DSAI3201

 - 3 2 3
DSAI4106 Embedded Systems & IoT INFT2101 - 3 2 3
Semester 10 Total: 12 7 15
SEMESTER 11
COMP4201 Capstone Project COMP4101 - 3 0 9
DSAI4103 Advanced Business Analytics MATH1040
DSAI3301		 - 3 2 3
Elective: Select 2 of 4          
DACS4203 IoT & OT Hacking DACS2201
INFS3102		 - 3 2 3
DSAI4201 Selected Topics in Data Science DSAI4101 - 3 2 3
DSAI4202 Information Retrieval DSAI3201 - 3 2 3
DSAI4205 Autonomous IoT DSAI3202 - 3 2 3
Semester 11 Total: 12 6 18
SEMESTER 12
COMP4301 Work Placement COMP4201 - 9 360 Total HRs
Semester 12 Total: 9 0 0
Year 4 Total: 33 13 33
B.Sc. DSAI Program Total: 126 87 92

 

 

 

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

Program Contact:

Dr. Bekir Ciftler
Department Head, Data Science and Artificial Intelligence
Email
bekir.ciftler@udst.edu.qa
Phone
+974-4495-2403