MSc in Artificial Intelligence

The Master of Artificial Intelligence program (Course-based) is thoughtfully designed to meet the needs of individuals seeking rewarding job prospects and working professionals aiming to advance their qualifications and elevate their careers in the fast-evolving field of artificial intelligence. This study plan has been prepared to deliver coherent and sequential knowledge through a state-of-the-are curriculum to the students. Hence, students shall be able to conduct high quality research and make contribution to meet the VISION 2030 of the kingdom. 

 

Bullseye with solid fill Vision

              Department of computer science envisages to be pioneer in providing world class education and research in the frontier areas of computer science and its applications.

 

Bullseye with solid fillMission

To provide a high-quality program for Artificial Intelligence aspirants that meets the labor market demands, research trends, and innovation, and contributes to the development of society and industry for achieving the national goals.

 

Target with solid fillGoals

  1. Provide competitive scientific and technical educational environment targeting towards professional excellence. 

  2. Encourage fundamental and applied research in fulfilling the professional needs of the computing industry.

     

Target with solid fillProgram Objectives

  1. Independently solve business problems using Artificial Intelligence.

  2. Pursue academic excellence through advanced study and continued research leading to professional development.

  3. Demonstrate active engagement and leadership to promote professional and organizational goals that address the needs of the community.

 

Clipboard Checked with solid fillProgram Learning Outcomes

  1. Demonstrate an understanding of mathematical concepts, algorithmic principles, and artificial intelligence theoretical knowledge.

  2. Analyze and assess emerging technological developments applied to artificial intelligence.

  3. Design, develop, and optimize Artificial Intelligence algorithms for real-world problems.

  4. Explore and identify learning and technical resources needed to adopt an AI strategy

  5. Present innovative architectural AI designs through strong communication skills.

  6. Demonstrate professional ethics and governance, to ensure successful AI project delivery

  7. Lead informed, strategic decision-making and augment business performance by integrating key AI management and leadership insights with societal concerns.

 

Clipboard Checked with solid fillGraduate Attributes

  1. Competitive Knowledge: High technical competencies to identify, design, implement and evaluate computing-based solutions with recent techniques

  2. Critical Thinking: Analytical and critical spirit to participate in the implementation of innovative computing solutions. 

  3. Exploratory Research: Scientific rigor to carry out state of the art research to investigate problems and derive innovative solution models.

  4. Effective communication: Communicate effectively to differed scientific level of audience in written and oral and to plan and manage collaborative research. 

  5. Social Responsibility: Sense of personal and social responsibility, following ethical and professional standards, leading to active participation and contribution to research society. 

  6. Adoptability: Adaptable to work environment with self-confidence and flexible nature. 

  7. Self-Learning: Capable to generate extensive knowledge through continued self learning.

 

Clipboard Checked with solid fillCareer Opportunities

  1. AI Engineer 

  2. Machine Learning Engineer/ Expert 

  3. Computer vision Engineer

  4. User Experience Design Engineer

  5. AI Research Scientist

  6. Lecturer/ Research Assistant

 

Settings with solid fill

Main Tracks

  1. Machine Learning.

  2. Computer Vision.

 

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Program Duration

The standard number of years in which a student can complete the program is 2 years (4 Semesters).

 

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Study Plan (33 Credit Hours)

 

 

 

Year 1

 

 

 

Semester I

 

 

Semester II

 

Code

Course Name

CH

Code

Course Name

CH

CS 6211

AI Foundations

3

CS 6221

Deep Learning

3

CS 6111

Mathematical Methods for Computing

3

CS 6213

Feature Engineering and Model Selection

3

CS 6212

Advanced Machine Learning

3

CS 6231

Computer Vision

3

  

9

  

9

      

 

 

Year 2

 

 

 

Semester III

 

 

Semester IV

 

Code

Course Name

CH

Code

Course Name

CH

CS 6222

Statistical Learning

3

***

Elective 2

3

***

Elective 1

3

CS 6241

Capstone Project

3

CS 6214

Time-Series Modeling

3

 

 

 

  

9

  

6

      
 

 

Tracks Electives

 

 

Track 1:

Machine Learning

 

Track 2:

Computer Vision

 

Code

Course Name

CH

Code

Course Name

CH

CS 6223

Reinforcement Learning

3

CS 6232

3D Imaging and Analysis

3

CS 6224

Natural Language Processing

3

CS 6233

Deep Learning in Computer Vision

3