3- Intended Learning Outcome :-

a- Knowledge and Understanding :-

a1) Understand some probabilistic and statistical analysis techniques.

a2) understand randomized algorithms and apply them in problem-solving.

a3) Locate and manage valuable information in large sets of unstructured data and semi-structured data from a variety of sources for database management systems.

a4) Locate and manage valuable information in large sets of unstructured data and semi-structured data from a variety of sources for data mining, geographical information systems, multimedia, enterprise systems,and human-computer interaction.

a5) Locate and manage valuable information in large sets of unstructured data and semi-structured data from a variety of sources for embedded systems, communications, e-commerice, multimedia, image processing, information and infrastructures security and computer graphics techniques.

a6) Apply AI techniques to the problem of acquisition .

a7) representation of expert knowledge for problem using various knowledge representation methods and different system structures from the industrial engineering point of view.

b- Intellectual Skills :-

b1) Identify criterias for better decision making.

b2) Deal with algorithm Design and Operations Research. 

c-Professional Skills :-

c1) Perform independent information acquisition and management, using the scientific literature and Web sources.

c2) perform Conceptual Models for Spatio-temporal Applications.

c3) study Spatio-temporal Models and Languages.

d-General Skills :-

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

d2) Effectively employ information-retrieval skills, (including the use of browsers.

d3) Effectively employ information-retrieval skills, (including the search engines, and on-line library catalogues).