Importance of AI, Knowledge Representation: Definition and importance of knowledge, representing single facts in logic, resolution non-monotonic reasoning, Dealing within inconsistencies and uncertainties, dempster shafrer theory, Ad-Ho methods, Heuristic reasoning methods, structural representation of knowledge graphs, frames and related structures. Neural Networks: Biological neuron, Artificial neurons and neural networks, Learning processes. Perceptron, multilayer layer perceptron, Bi-directional associative memory, Back propagation method, Self-organizing Kohonen networks, Hopfield neural network. Fuzzy Logic: Fuzzy set and control theory. Fuzzy inference, Fuzzy logic expert systems, Fuzzy associative memory, Fuzzy neural control. General algorithm, Pattern Recognition: Recognition and classification process, learning classification patterns, recognizing and understanding speech. Expert System: architectures, model based system, constraint satisfaction. Introduction to neural networks, learning algorithms and models.
Course Catalogue
Software Design.
Artificial Intelligence and Intelligent Agents, Problem Solving (Solving Problems by Searching, Adversarial Search, Constraint Satisfaction Problems), Knowledge and Reasoning (Logical Agents, First-Order Logic, Inference in First-Order Logic, Classical Planning, Planning and Acting in the Real World, Knowledge Representation), Uncertain Knowledge and Reasoning (Quantifying Uncertainty, Probabilistic Reasoning, Probabilistic Reasoning over Time, Making Simple Decisions, Making Complex Decisions), Learning (Learning from Examples, Knowledge in Learning, Learning, Probabilistic Models, Reinforcement Learning).
Introduction to machine learning; Regression analysis: Logistic regression, linear regression; Classification techniques: Supervised and unsupervised classification; Neural networks; Support vector machines; Classification trees; Rule based learning; Instance based learning; Reinforcement learning; Ensemble learning; Negative correlation learning; Evolutionary algorithms; Genetic algorithm, Statistical performance evaluation techniques of learning algorithms: bias-variance tradeoff; Practical applications of machine learning recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing.
Based on theory course.
Introduction to Software Engineering as a Discipline. Software Life Cycles. Software Requirement Specification and Analysis, Object Oriented Analysis and Design, Design patterns, Architectural patterns and scaling concern, Software Quality Assurance, Project management, Testing.
Introduction to computer networks: protocol layers, network performance Metrics-Delay, loss, throughput, jitter; circuit and packet switching; application layer: protocol overview of HTTP, FTP, SMTP, DNS, SNMP, P2P, client server and hybrid applications of the Internet; transport layer: protocol overview of TCP and UDP, principles of reliable data transfer, flow control, congestion control, TCP Reno, TCP Tahoe, socket programming; network layer: overview of IPv4 and IPv6, IP addressing, components of a router, routing and forwarding functions of a router, routing algorithms: link state and distance vector, OSPF and BGP; wireless networks: definition and types of wireless networks, MAC and routing in wireless networks, mobility and mobile IPv6.
Based on theory course.
Introduction to cyber security. Basic concepts: confidentiality, integrity, availability, security policies, security mechanisms, assurance. Basic Cryptography; Secret Key Cryptography, Message Digests, Public Key Cryptography; Authentication; Trusted Intermediaries; Real-time Communication Security; Electronic Mail Security; Firewalls and Web Security. Computer Security Management, Establishing and Managing Information Assurance, Forensics of Cyber Security, Hacking Techniques, Investigation and Response: Systems Forensics.
Introduction to information systems, general design consideration of information systems.
Overview: System concepts and the information systems environment, information needs, the concept of MIS, the 4-system development life cycle, the role of the systems analyst. Systems Analysis: System planning and the initial investigation, information gathering, the tools of structured analysis, feasibility study, cost/benefit analysis.
System design: The process and stage:; of systems design, input/output and forms design, file organization and data base design.
System Implementation: System testing and quality assurance implementation and software maintenance, hardware/ software selection, project scheduling and software; Security, disaster/recovery, and ethics in system development.
Caste studies of various information systems such as: Library management system, inventory system, voter identity management system, payroll system, etc.
Basic concept of telecomm network and wireless programming, The J2ME architecture, CDLC and KVM, The connected and limited devices configuration, Mobile information device profile, MIDP Programming, Low level user interface API, Event handling, Record management system, Network management, Using push registry in J2ME, SMS programming, .Net framework for wireless programming, Bluetooth and IrDA Communication, Programming PDA