Power Electronics and Clean Energy Systems (English) with thesis
Master	TR-NQF-HE: Level 7	QF-EHEA: Second Cycle	EQF-LLL: Level 7

General course introduction information

Course Code:

ECE535

Course Name:

Random Processes and Estimation

Course Semester:

Fall

Course Credits:

Theoretical	Practical	Credit	ECTS
		3	10

Language of instruction:

Course Requisites:

Does the Course Require Work Experience?:

Type of course:

Department Elective

Course Level:

Master

TR-NQF-HE:7. Master`s Degree

QF-EHEA:Second Cycle

EQF-LLL:7. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Dr.Öğr.Üyesi DİDEM KIVANÇ TÜRELİ

Course Lecturer(s):

Course Assistants:

Course Objective and Content

Course Objectives:

The aim of the course is to gain basic knowledge and abilities to the students about Combinatorial methods; product rule, permutation, combination. Probability; probability axioms, conditional probability, Bayes formula. Random variable; distribution function, probability function, Chebyshev inequality. Discrete and continuous distributions; uniform, Bernoulli, Poisson, geometric, hypergeometric, normal, exponential, gamma and beta distributions. Generating functions.

Course Content:

Combinatorial methods; product rule, permutation, combination. Probability; probability axioms, conditional probability, Bayes formula. Random variable; distribution function, probability function, Chebyshev inequality. Discrete and continuous distributions; uniform, Bernoulli, Poisson, geometric, hypergeometric, normal, exponential, gamma and beta distributions. Generating functions.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) Solve engineering problems using probability theory.
2) Solve engineering problems using random processes.
3) Formulate random theory based models of real life problems.
2 - Skills
Cognitive - Practical
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Lesson Plan

Week	Subject	Related Preparation
1)	Discrete Random Variables Continuous & General Random Variables	Read the relevant section of the textbook.
2)	Random Vectors Function of Random Variables Expectation, Variance, Conditional Expectation	Read the relevant section of the textbook.
3)	Bounds: Jensen, Markov, Chebyshev, Chernoff Law of Large Numbers, Central Limit Theorem Random Graphs	Read the relevant section of the textbook.
4)	Mini-Lab: Introduction to Python, Phase Transitions in Random Graphs, Auctions	Read the relevant section of the textbook.
5)	Discrete-Time Markov Chains (e.g., PageRank) Law of Large Numbers for Markov Chains	Read the relevant section of the textbook.
6)	Poisson Process	Read the relevant section of the textbook.
7)	Continuous-Time Markov Chains & Queues	Read the relevant section of the textbook.
8)	Mini-Lab & Project: Search Engines (PageRank), Digital Communication, Markov Decision Processes (e.g., Settlers of Catan)	Read the relevant section of the textbook.
9)	Statistical Inference Hypothesis Testing	Read the relevant section of the textbook.
10)	Maximum Likelihood Estimation	Read the relevant section of the textbook.
11)	Bayesian Inference	Read the relevant section of the textbook.
12)	Confidence Intervals	Read the relevant section of the textbook.
13)	Mini-Lab & Project: Real-world applications (e.g., Signal Processing, Communication Systems)	Read the relevant section of the textbook.
14)	Review	Review

Sources

Course Notes / Textbooks:	Probability and Statistics for Engineers and Scientists, Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye, Pearson Ed. ISBN 13: 978-0-321-62911-1
References:	Lecture Notes- Ders notları

Course-Program Learning Outcome Relationship

Learning Outcomes	1	2	3
Program Outcomes
1) Reaches the information in the field of power electronics and clean energy systems in depth through scientific researches; evaluates the knowledge, interprets and implements.
2) Has the extensive information about current techniques and their constraints in the field of Power Electronics .
3) Using limited or missing data, completes the information through scientific methods and applies; integrates the information from different disciplines.
4) Aware of new and emerging applications of his/her profession; learn and examine them if needed.
5) Builds the Power Electronics problems, develops methods to solve and implements innovative ways for solution.
6) Develops new and/or original ideas and methods; develops innovative solutions for the design of a process, system or component.
7) Designs and implements the analytical, modeling and experimental-based researches; resolves the complex situations encountered in this process and interprets.
8) Leads multi-disciplinary teams, develops solution approaches to complex situations and takes responsibility.
9) Uses at least one foreign language at the general level of European Language Portfolio B2 and communicates effectively in oral and written language.
10) Presents the process and results of the work in national and international media systematically and clearly in written or oral language.
11) Describe the social and environmental dimensions of Power Electronics Engineering applications.
12) In the stages of data collection, interpretation and publication as well as all professional activities, he/she considers the social, scientific and ethical values.

Course - Learning Outcome Relationship

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Reaches the information in the field of power electronics and clean energy systems in depth through scientific researches; evaluates the knowledge, interprets and implements.
2)	Has the extensive information about current techniques and their constraints in the field of Power Electronics .
3)	Using limited or missing data, completes the information through scientific methods and applies; integrates the information from different disciplines.
4)	Aware of new and emerging applications of his/her profession; learn and examine them if needed.
5)	Builds the Power Electronics problems, develops methods to solve and implements innovative ways for solution.
6)	Develops new and/or original ideas and methods; develops innovative solutions for the design of a process, system or component.
7)	Designs and implements the analytical, modeling and experimental-based researches; resolves the complex situations encountered in this process and interprets.
8)	Leads multi-disciplinary teams, develops solution approaches to complex situations and takes responsibility.
9)	Uses at least one foreign language at the general level of European Language Portfolio B2 and communicates effectively in oral and written language.
10)	Presents the process and results of the work in national and international media systematically and clearly in written or oral language.
11)	Describe the social and environmental dimensions of Power Electronics Engineering applications.
12)	In the stages of data collection, interpretation and publication as well as all professional activities, he/she considers the social, scientific and ethical values.

Learning Activity and Teaching Methods

Lesson
Reading
Problem Solving
Q&A / Discussion

Assessment & Grading Methods and Criteria

Written Exam (Open-ended questions, multiple choice, true-false, matching, fill in the blanks, sequencing)

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Midterms	2	% 50
Final	1	% 50
total		% 100
PERCENTAGE OF SEMESTER WORK		% 50
PERCENTAGE OF FINAL WORK		% 50
total		% 100

Workload and ECTS Credit Grading

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	15	3	45
Study Hours Out of Class	15	3	45
Midterms	2	15	30
Final	1	20	20
Total Workload			140