Curriculum for M.Sc./Ph.D.

Curriculum for M.Sc./Ph.D. in Electrical Engineering

Courses Description of EE

Two options for M.Sc. in Electrical Engineering, each with total credit hours of 30, are being offered:
(a)    Thesis Option: 8 Subjects (24 credit hours) + Research Thesis (6 credit hours)
(b)    Non-Thesis Option: 10 Subjects (30 credit hours)

(Only for programs offered on weekend)

Note: All courses are 3(3+0) credit hours each unless otherwise specified.

Course Code and Title
EE-502 Stochastic Processes
EE-503 Linear Systems Theory
EE-506 Engineering Mathematics
EE-510 Advanced Computer Architecture
EE-511 Advanced Computer Networks
EE-512 Machine Learning
EE-516 Image and Video Processing
EE-517 Design and Analysis of Algorithms
EE-519 Cybersecurity
EE-520 Wireless and Mobile Communications
EE-521 Information and Coding Theory
EE-522 Statistical Signal Processing
EE-524 Optical Communications
EE-525 Advanced Electromagnetic Theory
EE-527 Advanced VLSI System Design
EE-528 Antenna Theory and Design
EE-529 Advanced Microwave Circuits
EE-530 Power Electronics Converters
EE-535 Control of Electric Machines Drives
EE-541 Power System Dynamics and Stability
EE-547 Advanced Power Electronics
EE-549 High Voltage DC and Flexible AC Transmission
EE-550 Deep Learning
EE-551 Control of Power Equipment (2+1)
EE-552 Power Plant Dynamics (2+1)
EE-553 Power System Operation and Control (2+1)
EE-554 Advanced Power System Maintenance (2+1)
EE-555 Condition Monitoring of Equipment (2+1)
EE-556 Project Contract Management
EE-557 Environment Health and Safety
EE-558 Digital Control Systems (2+1)
EE-559 Instrumentation and Sensors (2+1)
EE-561 Array Signal Processing
EE-562 Adaptive Array Processing
EE-563 Micro-Electro-Mechanical-Systems (MEMS)
EE-570 Power System Transients and Insulation Coordination
EE-571 Power Inverters
EE-572 Smart Grids and Renewable Energy Systems
EE-599 Special Topics in Computer, Electronics & Communications, Power Systems
EE-611 Artificial Intelligence
EE-620 Advanced Wireless and Mobile Communications
EE-641 Advanced Power System Operation and Control
EE-642 Condition Monitoring of High Voltage Equipment
EE-643 Power System Reliability
Thesis
EE-699 M.Sc. Thesis in Electrical Engineering
EE-799 Ph.D. Thesis in Electrical Engineering
Curriculum for M.Sc. in Telecommunication Networks

Courses Description of Telecommunication Networks

Two options for M.Sc. in Telecommunication Networks, each with total credit hours of 30, are being offered:
(a)     Thesis Option: 8 Subjects (24 credit hours) + Research Thesis (6 credit hours)
(b)     Non-Thesis Option: 10 Subjects (30 credit hours) (Only for programs offered on weekend)

Note: All courses are 3 (3+0) credit hours each unless otherwise specified

Course Code and Title
Semester-I
TN-500: Mathematics for Networks
TN-520: Advanced Communication Systems
TN-530: Network Programming
Semester-II
TN-531: Software Defined Networking
TN-522: Optical Networks
TN-533: Network Security and Cryptography
Semesters-III, IV
TN-502: Optimization Theory
TN-550: Queuing Theory
TN-561: Next Generation Networks (3+1)
TN-562: Broadband Access Network (3+1)
TN-564: Radio Frequency Engineering (3+1)
Thesis
TN-699: M.Sc. Thesis in Telecommunication Networks
Curriculum for M.Sc. in Artificial Intelligence

Courses Description of Artificial Intelligence

The curriculum for the M.Sc. in Al requires two core courses, six electives, and a thesis (or two further electives if program offered on weekend): The elective courses are to be chosen from at least two different specializations. The specializations are:
1.        Applications of Artificial Intelligence

2.        Theoretical Foundations of Machine Learning

3.        Robotics

4.        Computational Models of Human Intelligence

Note: All courses are 3 (3+0) credit hours each unless otherwise specified.
Course Code and Title
AI-502: Artificial Intelligence     (Core course)
AI-503: Machine Learning       (Core course)
Applications of Artificial Intelligence
AI-511: Deep Learning
AI-512: Natural Language Processing
AI-513: Computer Vision
AI-514: Reinforcement Learning
Theoretical Foundations of Machine Learning
AI-521: Statistical Learning Theory
AI-522: Advanced Machine Learning
AI-523: Convex Optimization
AI-524: Probabilistic Graphical Models
AI-525: Special Topics in Machine Learning
AI-526: Mathematical and Computational Foundations for Artificial Intelligence
Robotics
AI-531: Modern Robotics
AI-532: Intelligent Control Systems
AI-533: Artificial Intelligence for Robotics
Computational Models of Human Intelligence
AI-541: Aspects of Computational Intelligence 
AI-542: Special Topics in Artificial Intelligence 
AI-543: Special Topics in Human Intelligence 
Thesis 
AI-699: M.Sc. Thesis in Artificial Intelligence