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.
Mission
We aim to offer a top-notch program tailored to individuals aspiring to specialize in artificial intelligence. This program is designed to meet the evolving demands of the labor market, stay abreast of the latest research trends, foster innovation, and play a pivotal role in advancing society and industry, thereby contributing to the achievement of national goals.
Program Objectives
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Independently solve business problems using Artificial Intelligence.
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Pursue academic excellence through advanced study and continued research leading to professional development.
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Demonstrate active engagement and leadership to promote professional and organizational goals that address the needs of the community.
Program Learning Outcomes
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Demonstrate an understanding of mathematical concepts, algorithmic principles, and artificial intelligence theoretical knowledge.
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Analyze and assess emerging technological developments applied to artificial intelligence.
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Design, develop, and optimize Artificial Intelligence algorithms for real-world problems.
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Explore and identify learning and technical resources needed to adopt an AI strategy
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Present innovative architectural AI designs through strong communication skills.
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Demonstrate professional ethics and governance, to ensure successful AI project delivery
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Lead informed, strategic decision-making and augment business performance by integrating key AI management and leadership insights with societal concerns.
Main Tracks
Machine Learning
Computer Vision
Duration
Two years (Four Semesters)
Study Plan (33 Credit Hours)
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Year 1 |
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Semester I |
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Semester II |
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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 |
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Year 2 |
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Semester III |
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Semester IV |
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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 |
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9 |
6 |
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Tracks Electives |
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Track 1: |
Machine Learning |
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Track 2: |
Computer Vision |
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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 |
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