Exam Type
This program is intended to impart the body of skills, knowledge and practices associated with the study of advanced computation, data science and AI, which will help to create new opportunities locally as well as globally. Specifically, three main thematic topics will be covered, viz., Neural Networks, Fuzzy system, Evolutionary Computation which form the backbone of intelligent systems. The curriculum includes multidisciplinary content covering Machine Learning, Neural Networks, Big Data Analytics, Information Retrieval, Fuzzy Systems and Evolutionary Computation. We will have opportunities to undertake practical projects, applying the learning to real-life problems prevalent in the domains like business, finance, security, industry control, engineering etc.
Objectives
The objectives of this program are as follows:
To provide the students with the knowledge of fundamental and complex topics in AI
To develop skills in the students to analyze large complex data.
To collaborate with AI-based national and international institutions to foster innovation, knowledge transfer and the R&D culture to meet the growing demands of the local and global markets.
Career Prospects
The program aims to produce graduates who are interested to do research and advance their career in the field of Artificial Intelligence. After the completion of the degree, graduates will be able to perform various jobs and research activities such as:
Computational Linguist,
AI Specialist,
Machine Learning Engineer,
Computer Vision Engineer
Data Scientist
Courses
Artificial Intelligence Cluster Core Courses
Code | Number | Subject Name | Credit Hours |
|---|---|---|---|
AICC | 500 | Artificial Intelligence | 2+1 |
AICC | 501 | Machine Learning | 2+1 |
AICC | 502 | Data Analytics | 2+1 |
AICC | 503 | Computational Intelligence | 2+1 |
AICC | 504 | Deep Neural Networks | 2+1 |
AICC | 505 | Intelligent Systems | 3 |
Artificial Intelligence Application Cluster
Code | Number | Subject Name | Credit Hours |
|---|---|---|---|
AIAC | 530 | Big Data Analytics (Bio, Health, WSN, Social Network, Financial Time Series) | 3 |
AIAC | 531 | Deep Learning | 2+1 |
AIAC | 532 | Internet of Things (Internet of Vehicle, Internet of Health, Internet of people) | 3 |
AIAC | 533 | Evolutionary Computation | 3 |
AIAC | 534 | Computer Vision | 2+1 |
AIAC | 535 | Image Processing | 2+1 |
AIAC | 536 | Natural Language Processing | 2+1 |
AIAC | 537 | Recommendation System | 2+1 |
AIAC | 538 | Intelligent Information Retrieval | 2+1 |
AIAC | 539 | Knowledge Representation and Reasoning | 3 |
AIAC | 550 | Expert System Design | 2+1 |
AIAC | 551 | Robotic Design | 2+1 |
AIAC | 552 | Human Computer Interaction | 3 |
AIAC | 553 | Software Design | 2+1 |
AIAC | 554 | Problem Solving Agents | 3 |
AIAC | 555 | Predictive Modeling | 2+1 |
AIAC | 556 | Quantum Computing | 2+1 |
Artificial Intelligence Mathematical Analysis
Code | Number | Subject Name | Credit Hours |
|---|---|---|---|
AIMA | 500 | Computational Statistics and Probability | 3 |
AIMA | 501 | Statistical Methods for AI Applications | 3 |
AIMA | 502 | Probabilistic Graphical Models | 3 |
AIMA | 503 | Fuzzy Systems | 3 |
AIMA | 504 | Discrete Multivariate Modeling | 3 |
AIMA | 505 | Computational Numerical Methods | 3 |
AIMA | 506 | Optimization Techniques | 3 |
Artificial Intelligence Research Work
Subject Area | Code | Subject Name | Credit Hours |
|---|---|---|---|
AIRW | 530 | Research Techniques for CS | 3 |
AIRW | 531 | Topics in Data Science | 3 |
AIRW | 532 | AI and Society | 3 |
AIRW | 533 | Topics in AI | 3 |
AIRW | 621 | Seminar | 3 |
AIRW | 699 | Thesis | 15 |
Artificial Intelligence Guided Course
Subject Area | Code | Subject Name | Credit Hours |
|---|---|---|---|
AIGC | 651 | Guided Course | 3 |
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