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Week
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Topics
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Study Metarials
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1
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Classification of data structures and data models and their basic properties
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K1-Chapter-2
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2
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Summarizing data models: linked list, trees, graphs, state machine data models
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K2-Chapter-8, K2-Chapter-9, K2-Chapter-10
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3
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State machine data model and sample applications
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K2-Chapter-14
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4
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Word search and application in the text with the state machine. Development of state machine application in a programming language
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K2-Chapter-14
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5
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Introduction to graph theory and representation of graphs: Neighborhood matrix
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K2-Chapter-12
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6
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Graph types and retention of graphs; sample applications
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K2-Chapter-12
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7
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The examination of problems such as graf coloration, shortest path algorithm, path tree
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K2-Chapter-12
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8
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Graf coloring and solving the problem of assignment assignment without overlap
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K2-Chapter-12
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9
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Shortest path algorithms: Dijkstra algorithm behavior, implementation and application of Dijkstra algorithm on the map
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K1-Chapter-2
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10
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Shortest path tree algorithms: Analysis and application of Kruskla algorithm
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K1-Chapter-2
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11
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Calculation of execution time and complexity of algorithms. Big O notation
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K3-Chapter-2
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12
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Compression algorithms and programs
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K2-Chapter-15
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13
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Huffman coding tree and sample application: Frequency of characters usage and Huffman tree creation
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K3-Chapter-4
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14
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Application development and grammar analysis algorithms on Probability Theory
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K3-Chapter-4
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Prerequisites
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-
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Language of Instruction
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Turkish
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Responsible
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Assist.Prof.Dr. Seda ŞAHİN
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Instructors
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-
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Assistants
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-
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Resources
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K1-Gonnet, G. H., (1984) Handbook Algorithms and Data Structure, Addision-Wesley Pub., 1984.
K2-Çölkesen, R., Data Structure and Algorithms, Papatya Publishing House, İstanbul, 1999.
K3-Çölkesen, R., Algorithm Development and Data Structures, Papatya Publishing House, İstanbul, 2011.
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Supplementary Book
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-
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Goals
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to model the problems encountered, selecting the most appropriate algorithms and data models.
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Content
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Classification of data structures and data models and their basic properties, Summarizing data models: linked list, trees, graphs, state machine data models, State machine data model and sample applications, Word search and application in the text with the state machine. Development of state machine application in a programming language, Introduction to graph theory and representation of graphs: Neighborhood matrix, Graph types and retention of graphs; sample applications, The examination of problems such as graf coloration, shortest path algorithm, path tree, Graf coloring and solving the problem of assignment assignment without overlap, Shortest path algorithms: Dijkstra algorithm behavior, implementation and application of Dijkstra algorithm on the map, Shortest path tree algorithms: Analysis and application of Kruskla algorithm, Calculation of execution time and complexity of algorithms. Big O notation, Compression algorithms and programs, Huffman coding tree and sample application: Frequency of characters usage and Huffman tree creation, Application development and grammar analysis algorithms on Probability Theory
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Program Learning Outcomes |
Level of Contribution |
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1
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To be able to apply mathematics, science and engineering theories and principles to Computer Engineering problems.
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4
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2
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To have the ability to define, model, and solve problems related to Computer Engineering.
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4
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3
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To be able to design and conduct experiments, as well as to analyze and interpret data.
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3
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4
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To be able to design and analyze a process for a specific purpose within technical and economical limitations.
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-
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5
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To be able to use modern techniques and calculation tools required for engineering applications.
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-
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6
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To have the awareness of professional liabilities and ethics.
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-
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7
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To be able to get involved in interdisciplined and multidisciplined team work.
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-
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8
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To be able to declare his/her opinions orally or written in a clear, concise and brief manner.
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-
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9
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To improve him/herself by following the developments in science, technology, modern issues, and know the importance of lifelong learning.
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-
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10
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To be able to evaluate engineering solutions for the global and social problems especially for the health, safety, and environmental problems.
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-
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11
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To have knowledge about of contemporary issues.
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-
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