SPEECH AND LANGUAGE THERAPY
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Ders Genel Tanıtım Bilgileri

Course Code:

CMP3005

Ders İsmi:

Analysis of Algorithms

Ders Yarıyılı:

Spring
Fall

Ders Kredileri:

Theoretical	Practical	Credit	ECTS
3	0	3	6

Language of instruction:

English

Ders Koşulu:

Ders İş Deneyimini Gerektiriyor mu?:

Type of course:

Non-Departmental Elective

Course Level:

Bachelor

TR-NQF-HE:6. Master`s Degree

QF-EHEA:First Cycle

EQF-LLL:6. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Dr. Öğr. Üyesi CEMAL OKAN ŞAKAR

Course Lecturer(s):

Course Assistants:

Dersin Amaç ve İçeriği

Course Objectives:

The objective of the course is to introduce the fundamental mathematical tools needed to analyze algorithms, basic algorithm design techniques, advanced data structures, and important algorithms from different problem domains.

Course Content:

Introduction, asymptotic notation, empirical analysis of algorithms, designing algorithms, amortized analysis, brute force algorithms, divide and conquer algorithms, transform and conquer algorithms, space and time trade-offs, dynamic programming, greedy algorithms, advanced data structures, B-trees, Insertion and Deletion from B-trees, graphs and graph algorithms, P, NP, and NP-complete problems.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
2 - Skills
Cognitive - Practical
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Ders Akış Planı

Week	Subject	Related Preparation
1)	Introduction, asymptotic notation.
2)	Empirical analysis of algorithms, analysis of algorithms, amortized analysis
3)	Recurrences, substitution method, recursion-tree method, master method.
4)	Brute Force Algorithms
5)	Divide and Conquer Algorithms
6)	Merge sort, quicksort, randomized quicksort, binary search
7)	Transform and Conquer Algorithms: Solving systems of linear equations with Gaussian ination elimination, Balanced Search Trees, Heaps and Heapsort, Horner's Rule and Binary Exponentiation
8)	Space and Time Trade-offs: Input Enhancement (Counting based sorting, string matching), Prestructuring (Hashing, Hash functions, open addressing).
9)	Midterm
10)	Dynamic Programming: Coin-row problem, Knapsack problem, Longest common subsequence.
11)	Dynamic Programming: Knapsack problem, Longest common subsequence.
12)	Greedy Algorithms: Activity selection, Huffman codes, Prim’s algorithm, Kruskal’s Algorithm
13)	Single-source shortest paths: The Bellman-Ford algorithm, Dijkstra's algorithm.
14)	P, NP, and NP-complete problems

Sources

Course Notes / Textbooks:	Anany Levitin, The Design and Analysis of Algorithms, Pearson International Third Edition. Cormen, T. H., Leiserson, C. E., Rivest, R. L. and Stein, C., Introduction to Algorithms (3rd Edition), MIT Press, 2009. Sanjoy Dasgupta , Christos Papadimitriou, Umesh Vazirani, Algorithms, McGraw-Hill Education.
References:	Yok - None

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları
Program Outcomes
1) To use theoretic and methodological approach, evidence-based principles and scientific literature in Speech and Language Therapy field systematically for practice.
2) To have theoretic and practical knowledge for individual's, family's and the community's health promotion and protection.
3) To use information and health technologies in practice and research in the field of Speech and Language Therapy.
4) To communicate effectively with advisee, colleagues for effective professional relationships.
5) To be able to monitor occupational information using at least one foreign language, to collaborate and communicate with colleagues at international level.
6) To use life-long learning, problem-solving and critical thinking skills.
7) To act in accordance with ethical principles and values in professional practice.
8) To take part in research, projects and activities within sense of social responsibility and interdisciplinary approach.
9) To be able to search for literature in health sciences databases and information sources to access to information and use the information effectively.
10) To take responsibility and participate in the processes actively for training of other therapist, education of health professionals and individuals about speech and languege therapy.
11) To carry out speech and languge therapy practices considering cultural differences and different health needs of different groups in the community.

Ders - Öğrenme Kazanımı İlişkisi

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

	Program Outcomes	Level of Contribution
1)	To use theoretic and methodological approach, evidence-based principles and scientific literature in Speech and Language Therapy field systematically for practice.
2)	To have theoretic and practical knowledge for individual's, family's and the community's health promotion and protection.
3)	To use information and health technologies in practice and research in the field of Speech and Language Therapy.
4)	To communicate effectively with advisee, colleagues for effective professional relationships.
5)	To be able to monitor occupational information using at least one foreign language, to collaborate and communicate with colleagues at international level.
6)	To use life-long learning, problem-solving and critical thinking skills.
7)	To act in accordance with ethical principles and values in professional practice.
8)	To take part in research, projects and activities within sense of social responsibility and interdisciplinary approach.
9)	To be able to search for literature in health sciences databases and information sources to access to information and use the information effectively.
10)	To take responsibility and participate in the processes actively for training of other therapist, education of health professionals and individuals about speech and languege therapy.
11)	To carry out speech and languge therapy practices considering cultural differences and different health needs of different groups in the community.

Öğrenme Etkinliği ve Öğretme Yöntemleri

Ölçme ve Değerlendirme Yöntemleri ve Kriterleri

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Quizzes	2	% 10
Project	1	% 20
Midterms	1	% 30
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 60
PERCENTAGE OF FINAL WORK		% 40
Total		% 100

İş Yükü ve AKTS Kredisi Hesaplaması

Activities	Number of Activities	Workload
Course Hours	14	42
Project	7	21
Quizzes	6	12
Midterms	5	28
Final	5	35
Total Workload		138