| GASTRONOMY (TURKISH) | |||||
| Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 | ||
| Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
| CMP3005 | Analysis of Algorithms | Spring | 3 | 0 | 3 | 6 |
| This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester. |
| Language of instruction: | English |
| Type of course: | Non-Departmental Elective |
| Course Level: | Bachelor’s Degree (First Cycle) |
| Mode of Delivery: | Face to face |
| Course Coordinator : | Dr. Öğr. Üyesi CEMAL OKAN ŞAKAR |
| Course Lecturer(s): |
Dr. Öğr. Üyesi TEVFİK AYTEKİN Prof. Dr. NAFİZ ARICA Dr. Öğr. Üyesi CEMAL OKAN ŞAKAR |
| Recommended Optional Program Components: | None |
| 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. |
|
The students who have succeeded in this course; I. Become familiar with some major advanced data structures and algorithms. II. Become familiar with mathematical tools used in analyzing algorithms. III. Be able to analyze the asymptotic running time of an (iterative/recursive) algorithm. IV. Be able to make best/worst/average case analysis of algorithms. V. Become familiar with important algorithm design paradigms. VI. Be able to decide which data structure/algorithm among a set of possible choices is best for a particular application. VII. Be able to recognize and distinguish efficient and inefficient algorithms. VIII. Be able to design efficient algorithms for new problems using the techniques learned and apply/report these solutions in an intra-discipline project group. |
| 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. |
| 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 |
| 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 |
| 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 | % 40 | |
| PERCENTAGE OF FINAL WORK | % 60 | |
| Total | % 100 | |
| Activities | Number of Activities | Workload |
| Course Hours | 14 | 42 |
| Project | 7 | 21 |
| Quizzes | 6 | 12 |
| Midterms | 5 | 28 |
| Final | 5 | 35 |
| Total Workload | 138 | |
| No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
| Program Outcomes | Level of Contribution | |
| 1) | - Possess advanced level theoretical and practical knowledge supported by textbooks with updated information, practice equipments and other resources. | |
| 2) | Use of advanced theoretical and practical knowledge within the field. -Interpret and evaluate data, define and analyze problems, develop solutions based on research and proofs by using acquired advanced knowledge and skills within the field. | |
| 3) | Inform people and institutions, transfer ideas and solution proposals to problems in written and orally on issues in the field. - Share the ideas and solution proposals to problems on issues in the field with professionals and non-professionals by the support of qualitative and quantitative data. -Organize and implement project and activities for social environment with a sense of social responsibility. -Monitor the developments in the field and communicate with peers by using a foreign language at least at a level of European Language Portfolio B1 General Level. -Use informatics and communication technologies with at least a minimum level of European Computer Driving License Advanced Level software knowledge. | |
| 4) | Evaluate the knowledge and skills acquired at an advanced level in the field with a critical approach. -Determine learning needs and direct the learning. -Develop positive attitude towards lifelong learning. | |
| 5) | Act in accordance with social, scientific, cultural and ethic values on the stages of gathering, implementation and release of the results of data related to the field. - Possess sufficient consciousness about the issues of universality of social rights, social justice, quality, cultural values and also, environmental protection, worker's health and security. | |
| 6) | Conduct studies at an advanced level in the field independently. - Take responsibility both as a team member and individually in order to solve unexpected complex problems faced within the implementations in the field. - Planning and managing activities towards the development of subordinates in the framework of a project |