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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EEE 5041 COMPUTER ALGORITHMS - I ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR MUSTAFA ALPER SELVER

Offered to

ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH) ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH) ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH)

Course Objective

Students are able to learn widely used computer algorithms in all fields of engineering, the motivation behind the use of these algorithms, their algorithms parameters to determine the "best" or "most desirable" solution to a problem.

Learning Outcomes of the Course Unit

1   The students are expected to learn algorithmic approaches for sorting. 2   The students are expected to learn algorithmic approaches for multi-dimensional data analysis. 3   The students are expected to learn algorithmic approaches for networking probles such as minimal path, spanning tree determination. 4   The students are expected to solve real world programming problems by writing programmes learned during the lecture. 5   The students are expected to prepare a technical report related with the term project.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction to techniques and application areas 2 Analyze worst-case running times of algorithms 3 Describe the dynamic-programming paradigm and explain when an algorithmic design situation calls for it. 4 Recite algorithms that employ dynamic-programming paradigm. Synthesize dynamic-programming algorithms, and analyze them. 5 Describe the greedy paradigm and explain when an algorithmic design situation calls for it. 6 Recite algorithms that employ greedy paradigm. Synthesize greedy algorithms, and analyze them. 7 Explain the major algorithms for shortest path. Recite the analyses of these algorithms and the design strategies that the algorithms embody. 8 Synthesize algorithms that employ shortest path as a subprocedure. Derive lower bounds on the running time of comparison-sorting algorithms, and explain how these bounds can be overcome. 9 Explain the major network flow algorithms and their analyses 10 Explain the major graph algorithms and their analyses. 11 Synthesize new graph algorithms and algorithms that employ graph computations as key components, and analyze them. 12 Describe the divide-and-conquer paradigm and explain when an algorithmic design situation calls for it. 13 Recite algorithms that employ this paradigm. Synthesize divide-and-conquer algorithms. Derive and solve recurrences describing the performance of divide-and-conquer algorithms. 14 Term project presentations

Recomended or Required Reading

Cormen, Leiserson, Rivest and Stein, Introduction to Algorithms, 2nd Edition

Planned Learning Activities and Teaching Methods

Lectures, Homeworks, Term project

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 ASG ASSIGNMENT 2 PRS PRESENTATION 3 FCG FINAL COURSE GRADE ASG * 0.50 + PRS * 0.50

Further Notes About Assessment Methods

None

Assessment Criteria

term projects, homeworks

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

alper.selver@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 14 3 42 Preparing assignments 10 8 80 Preparing presentations 1 30 30 Preparations before/after weekly lectures 14 3 42 TOTAL WORKLOAD (hours) 194

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 PO.11 PO.12 PO.13 PO.14 LO.1 5 4 4 3 5 1 2 2 2 1 4 2 1 1 LO.2 5 4 4 4 5 2 3 1 2 2 5 2 1 1 LO.3 5 4 5 5 5 5 3 3 3 4 5 4 2 2 LO.4 5 4 4 3 5 2 2 2 2 2 4 2 1 1 LO.5 3 4 4 1 2 1 1 5 4 2 2 1 1 1