3- Intended Learning Outcome :-

a- Knowledge and Understanding :-

a1- Understand theories, fundamentals, and current state-of-the-art in information technology domain and their related domains.

a2- Understand and analyze methods for automatic training of classification systems based on typical statistical, syntactic and neural network approaches.

a3- Understand the concept of Image Features, Object Matching and Recognition, Statistical Approaches to Pattern Recognition and Neural Networks and Their Applications to Pattern Recognition.

a4- Understand common feature extraction methods for pattern recognition.

a5- Know how the stages of projects are managed within differing methodologies, and the implications for adherence to quality assurance standards.

a6- Know the nature of the development change within the industry, and the impact that this has on the management and implementation of IT Systems.

b-Intellectual Skills :-

b1- Carry out new research studies or write scientific papers in information technology

b2- Design systems and algorithms for pattern recognition.

b3- Designing SVM system.

b4- Design of Statistical Classifiers.

b5- Design of Neural Network PR Systems.

b6- Deliver a major piece of research (via dissertation) in the domain.

c-Professional Skills :-

c1- Evaluate professional reports related to information technology.

c2- Implement typical pattern recognition algorithms in MATLAB.

c3- Prepare technical reports, and a dissertation, to a professional standard; use IT skills and display mature computer literacy.

c4-  Analysis Approaches to Pattern Recognition.

d-General Skills :-

d1- Search for information and adopt life-long self-learning.

d2- Think critically and learn independently.