Advanced Algorithmic Topics (ΠΛ3): Διαφορά μεταξύ των αναθεωρήσεων
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! Learning outcomes | ! Learning outcomes | ||
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The goal of this course is the deeper understanding of the design and analysis of algorithms and address specific classes of problems and algorithms to solve them as well as the introduction of students to critical thinking and research process. A detailed examination of advanced methods of analysis and design of algorithms is done during the course. The analysis of an algorithm studies ways of finding its complexity. For the design of an algorithm for a problem we discuss basic design methods such as: greedy methods, dynamic programming, backtracking, recursion, exhaustive search of solution space, and branch and bound. We examine algorithms for problem categories such as sorting, searching, selection, graphs processing, integers and polynomials arithmetic, algorithms in matrices, and string handling algorithms. Complexity classes such as P, NP, NP-complete are defined. Some specific topics are also presented. After completing the course the student: | |||
* Can analyze an algorithm | |||
* Can select the most effective algorithm between algorithms for solving a problem. | |||
* Has a good understanding of design methods and can design efficient algorithms for solving a problem. | |||
* Knows algorithms to solve basic categories of problems and can use them as a building block for the design of other algorithms. | |||
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! General Competences | ! General Competences | ||
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* Independent work | |||
* Bibliographic search | |||
* Complexity analysis of an algorithm | |||
* Effective selection of an algorithm to solve a problem | |||
* Design of efficient algorithms for the solution of a problem | |||
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Αναθεώρηση της 17:23, 10 Νοεμβρίου 2022
Graduate Courses Outlines - Department of Mathematics
General
| School | School of Science |
|---|---|
| Academic Unit | Department of Mathematics |
| Level of Studies | Graduate |
| Course Code | ΠΛ3 |
| Semester | 1 |
| Course Title | Advanced Algorithmic Topics |
| Independent Teaching Activities | Lectures (Weekly Teaching Hours: 3, Credits: 7.5) |
| Course Type | Specialization |
| Prerequisite Courses |
Undergraduate courses in Data structures and Algorithms (optionally a course in Discrete mathematics) |
| Language of Instruction and Examinations |
Greek |
| Is the Course Offered to Erasmus Students | Yes (in English) |
| Course Website (URL) | See eCourse, the Learning Management System maintained by the University of Ioannina. |
Learning Outcomes
| Learning outcomes |
The goal of this course is the deeper understanding of the design and analysis of algorithms and address specific classes of problems and algorithms to solve them as well as the introduction of students to critical thinking and research process. A detailed examination of advanced methods of analysis and design of algorithms is done during the course. The analysis of an algorithm studies ways of finding its complexity. For the design of an algorithm for a problem we discuss basic design methods such as: greedy methods, dynamic programming, backtracking, recursion, exhaustive search of solution space, and branch and bound. We examine algorithms for problem categories such as sorting, searching, selection, graphs processing, integers and polynomials arithmetic, algorithms in matrices, and string handling algorithms. Complexity classes such as P, NP, NP-complete are defined. Some specific topics are also presented. After completing the course the student:
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| General Competences |
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Syllabus
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