Master of Science in Data Science and Artificial Intelligence (M.Sc. DSAI)

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Program Description:

The Master of Science in Data Science and Artificial Intelligence (M.Sc. DSAI) is a dynamic, two-year postgraduate program designed to equip students with the essential knowledge and skills for a successful career in the rapidly evolving fields of Data Science (DS) and Artificial Intelligence (AI). This program blends core courses in DS and AI providing a comprehensive understanding and integration of these two critical domains. Students gain the ability to analyze complex datasets, develop AI models, and implement innovative solutions to address real-world challenges across diverse industries, fostering their ability to make data-driven decisions and drive impactful change.

Key features of the program include an interdisciplinary core curriculum, specialization tracks, practical application and theory, professional development, and preparation for the future. Upon completion, graduates possess a unique combination of skills, ready to address the challenges of DS and AI in various roles across industries. This program is not just a pathway to a career; it is a gateway to becoming a leader in a field that drives innovation, shapes the future of technological advancement, and in indispensable for addressing the data-driven challenges of today’s interconnected world.

Program Duration:

Two years

Admission Requirements:

1. Bachelor degree in Data Science and/or Artificial Intelligence from an accredited higher education institution with a minimum GPA of 3.0 on a 4.0 scale. In addition, bridging courses may be required;

OR

2. Bachelor degree in a related discipline, such as Computer Science, Information Systems, IT, Software Engineering, Electronic Engineering, Bioinformatics, Mathematics, Statistics, or any other field with a strong quantitative, computational, or engineering orientation, from an accredited higher education institution with a minimum GPA of 3.0 on a 4.0 scale. In addition, bridging courses may be required.

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 score of 6.0, with no individual band score (reading, writing, speaking, and listening) below 6.0;

OR

3. A valid (within two years) TOEFL score of 90 and minimum scores of 17 in listening, 18 in reading, 20 in speaking, and 35 in writing;

OR

4. A valid (within two years) iBT score of 72. 

 

Applicants are expected to have a proficient understanding of calculus, linear algebra, probability, and statistics at the undergraduate level.

1. Academic transcripts related to the Bachelor degree and/or post graduate diploma presented upon application;

AND

2. A satisfactory performance in the personal interview with the Admissions Committee.

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 Master of Science in Data Science and Artificial Intelligence (M.Sc. DSAI) program, graduates will be able to:

PEO01. Synthesize advances in DS and AI to design, develop, deploy, and evaluate innovative solutions capable of tackling complex challenges in diverse sectors

PEO02. Develop and implement policies and procedures that support efficient and strategic decision-making, ensuring adherence to best practices in data governance and AI

PEO03. Adhere to legal regulations and ethical standards in the design, development, verification, and deployment of DS and AI systems while making informed decisions that consider their broader impacts on the economy, environment, and society

PEO04. Develop and demonstrate leadership and collaborative skills in interdisciplinary teams, fostering impactful innovation and promoting continuous learning in DS and AI initiatives

PEO05. Engage in lifelong learning and continuous professional development within the evolving disciplines of DS and AI

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 Master of Science in Data Science and Artificial Intelligence (M.Sc. DSAI) program, graduates will be prepared to:

SLO01. Evaluate theories and techniques of DS and AI for designing solutions to complex problems

SLO02. Apply advanced DS and AI principles to design, develop, deploy, and evaluate practical solutions to complex problems

SLO03. Employ DS and AI solutions to optimize processes and provide actionable insights to support informed decision-making

SLO04. Utilize responsible AI principles and data governance in the design of DS and AI systems

SLO05.Demonstrate professional and ethical responsibilities in DS and AI, considering the impact on the economy, environment, and society

SLO06. Function collectively and independently as a team member or leader in DS and AI activities, driving innovation and collaboration while upholding the highest ethical standards

Study Plan:

COURSE
NUMBER		 COURSE TITLE requisite HOURS/WEEK
PRE-req CO-req CR LEC LAB
SEMESTER 1
DSAI5101 Principles of Data Science & Machine Learning  - - 3 2 3
AICC5102 Principles of AI  - - 3 2

3
DSAI5102 Data Architecture & Engineering  - - 3 2 3
Semester 1 Total: 9 6 9
SEMESTER 2
DSAI5201 Data governance & Responsible AI  DSAI5101 - 3 2 2
DSAI5202 Advanced Deep Learning  - - 3 2 3
AICC5204 Research Methods & Professional Development 

-

 - 3 3 0
Semester 2 Total: 9 7 5
Year 1 Total: 18 13 14
COURSE
NUMBER		 COURSE TITLE requisite HOURS/WEEK
PRE-req CO-req CR LEC LAB
SEMESTER 3
DSAI6101 Advanced Natural Language Processing  DSAI5101 - 3 2 3
AICC6103 Computing Seminar  AICC5204 - 1 1 0
Elective - Select 1 of 3
DSAI6102 Advanced Computer Vision  DSAI5202 - 3 2 3
DSAI6103 Advanced Reinforcement Learning  DSAI5101 - 3 2 3
AICC6102 AI Systems Engineering  AICC5202 OR DSAI5102 - 3 2 3
Research or Professional Track- Select 1 of 2 
AICC6104 Computing Research Thesis Project 1  AICC5204 - 3 0 9
AICC6110 Selected Topics for Computing Graduation Project AICC5202 OR DSAI5101 - 3 3 0
Semester 4 Research Track Total: 10 5 15
Semester 4 Professional Track Total: 10 8 6
SEMESTER 4
Research or Professional Track: Select 1 of 2
AICC6204 Computing Research Thesis Project II AICC5204 & AICC6104 - 3 0 9
AICC6210 Computing Graduation Project AICC5204 & AICC6110 - 3 0 9
Elective - Select 1 of 3
DSAI6201 Business Intelligence & Data Analytics DSAI5101 - 3 2 3
DSAI6202 Software Engineering for Machine Learning Systems  DSAI5101 - 3 2 3
DSAI6203 AI in Healthcare DSAI5101 - 3 2 2
DSAI6205 Generative AI & LLMs DSAI5102 - 3 2 3
Semester 4 Research Track Total: 6 2 12
Semester 4 Professional Track Total: 6 2 12
Year 2 Research Track Total: 16 7 27
Year 2 Professional Track Total: 16 10 18
M.Sc. DSAI Program Total (Research Track): 34 20 41
M.Sc. DSAI Program Total (Professional Track): 34 23 32

 

 

Graduate Future Pathways:

Graduates of the Master of Science in Data Science and Artificial Intelligence (M.Sc. DSAI) program may choose to engage in advanced research and development, policy and regulation, entrepreneurship and startups, corporate leadership and strategy, educational and academic contributions, industry-specific applications, international development and data-driven innovation, technology consulting, public sector and governmental roles, and ethics and responsible AI. 

Career Opportunities:

The Master of Science in Data Science and Artificial Intelligence (M.Sc. DSAI) program is an applied degree 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: 

  • Senior Data Science Strategist 

  • AI & Machine Learning Engineer 

  • Big Data Analytics Expert 

  • Data Architecture & Infrastructure Specialist 

  • Operations Research & Optimization Analyst 

  • Actuarial & Risk Management Analyst 

  • Computational Research Scientist in AI 

  • Ethical AI Policy & Governance Advisor 

  • Market Insights & Survey Analytics Expert 

  • Data-Driven Innovation Consultant 

 

Dr. Reda Bendraou
Coordinator for Postgraduate Programs
Email
reda.bendraou@udst.edu.qa
Phone
+974- 4495 2034