The Master of Artificial Intelligence (Courses-based) program is intended for working professionals who are eager to enhance their qualifications in order to achieve growth in their careers.
Mission
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.
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 (Six Trimesters)
Study Plan (45 Credit Hours)
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Year 1 |
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Semester I |
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Semester II |
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Semester III |
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Code |
Course Name |
CH |
Code |
Course Name |
CH |
Code |
Course Name |
CH |
CS 6211 |
AI Foundations |
4 |
CS 6212 |
Advanced Machine Learning |
4 |
CS 6221 |
Deep Learning |
4 |
CS 6111 |
Mathematical Methods for Computing |
4 |
CS 6231 |
Computer Vision |
4 |
CS 6213 |
Feature Engineering and Model Selection |
4 |
8 |
8 |
8 |
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Year 2 |
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Semester IV |
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Semester V |
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Semester VI |
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Code |
Course Name |
CH |
Code |
Course Name |
CH |
Code |
Course Name |
CH |
CS 6222 |
Statistical Learning |
4 |
CS 6214 |
Time-Series Modeling |
4 |
CS 6241 |
Capstone Project |
5 |
*** |
Elective 1 |
4 |
*** |
Elective 2 |
4 |
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8 |
8 |
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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 |
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Code |
Course Name |
CH |
CS 6223 |
Reinforcement Learning |
4 |
CS 6232 |
3D Imaging and Analysis |
4 |
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CS 6224 |
Natural Language Processing |
4 |
CS 6233 |
Deep Learning in Computer Vision |
4 |
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4 |
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4 |