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- Outline the application areas of detection and estimation theories in various sub-disciplines of electrical engineering.

a3- Understand Scientific developments in information technology.

a4- Categorize the estimation approaches based on the characteristics of the parameters of interest.

a5- Quality principles for professional practice in information technology.

a6- Use hypothesis testing and Bayesian approaches to formulate and solve problems for signal detection from noisy signals.

a7- Use classical and Bayesian approaches to formulate and solve problems for parameter estimation from noisy signals.

b-Intellectual Skills :-

b1- Analyze and evaluate the information in the domain of information technology.

b2- Evaluate the estimator performance through the derivation of Cramer-Rao bound.

b3- Solve specialized problems based on the available inputs.

b4- Identify the nature of hypothesis testing, i.e., simple versus composite.

b5- Apply the above tests to derive the optimum detection rule based on a given set of observation

b6- Derive and apply linear filtering methods for parameter estimation and signal smoothing

c-Professional Skills :-

c1- produce work which is at the forefront of the study domain, including critical evaluation of the domain's aspects.

c2- Design deterministic parameter estimators to minimize the estimator variance.

c3- Design random parameter estimators based on the Bayesian approach.

d-General Skills :-

d1- Describe a self-assessment and determine its education and personal requirements.

d2- present students with applications of detection and estimation theories in various sub-disciplines of electrical engineering.

d3- Be capable of applying both traditional and new concepts and skills.