Algorithms and Advanced Programming II(MAT232)
| Course Code | Course Name | Semester | Theory | Practice | Lab | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| MAT232 | Algorithms and Advanced Programming II | 4 | 3 | 0 | 0 | 3 | 5 |
| Prerequisites | |
| Admission Requirements |
| Language of Instruction | French |
| Course Type | Compulsory |
| Course Level | Bachelor Degree |
| Course Instructor(s) | N. Sultan TURHAN sturhan@gsu.edu.tr (Email) |
| Assistant | |
| Objective | The purpose of this course is to improve students understanding of algorithm design and analysis by studying algorithms working on more complex data structures. |
| Content |
1. Introduction to object-oriented programming - Basic Concepts 2. Trees and tree hopping 3. AVL Trees 4. Splay Trees 5. Max and Min Stack Trees 6. MultiWays Tree 7. Graphs and Entanglement Algorithms 8. Minimum Spanning Tree 9. Graph algorithms (shortest path, all pairs shortest path, Djikstra's algorithm) 10. Coloring of graphs, matrix representation, conversion between representations in the form of matrices and objects 11. Character Sequence Algorithms (search in character sequence, longest common substring) 12. Reference behavior, value behavior, shallow/deep copy |
| Course Learning Outcomes |
When given a problem over a proprietary data structure, students will be able decompose the data structure and computation workflow to known cases and implementations. When given the description of a new algorithm, students will be able to implement it in a programming language relying on implementation experience gained from this course. When given a source code, students will be able to identify data structures and algorithms that are implemented in the given source code. |
| Teaching and Learning Methods | lecture, programming home work, presentation |
| References |
The Art of Computer Programming, Addison-Wesley, Donald Knuth Algorithms, 4th Ed. Robert Sedgewick Lafore, R., Broder, A., & Canning, J. (2022). Data Structures and Algorithms in Python. Pearson Education, Limited. Agarwal, B., & Baka, B. (2018). Hands-On Data Structures and Algorithms with Python: Write complex and powerful code using the latest features of Python 3.7. Packt Publishing Ltd. www.geeksforgeeks.org |
Theory Topics
| Week | Weekly Contents |
|---|
Practice Topics
| Week | Weekly Contents |
|---|
Contribution to Overall Grade
| Number | Contribution | |
|---|---|---|
| Contribution of in-term studies to overall grade | 7 | 65 |
| Contribution of final exam to overall grade | 1 | 35 |
| Toplam | 8 | 100 |
In-Term Studies
| Number | Contribution | |
|---|---|---|
| Assignments | 5 | 15 |
| Presentation | 0 | 0 |
| Midterm Examinations (including preparation) | 1 | 25 |
| Project | 1 | 25 |
| Laboratory | 0 | 0 |
| Other Applications | 0 | 0 |
| Quiz | 0 | 0 |
| Term Paper/ Project | 0 | 0 |
| Portfolio Study | 0 | 0 |
| Reports | 0 | 0 |
| Learning Diary | 0 | 0 |
| Thesis/ Project | 0 | 0 |
| Seminar | 0 | 0 |
| Other | 0 | 0 |
| Toplam | 7 | 65 |
| No | Program Learning Outcomes | Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | understands principles of deductive reasoning; has experience to verify well-foundedness and exactness of mathematical statements in systematic ways; | |||||
| 2 | can properly state and use concepts and results of major mathematical interest; | X | ||||
| 3 | masters current computational techniques and algorithms; has a good ability in their use; can identify relevant tools, among those one has learned, suitable to solve a problem and is able to judge whether or not one is in possession of these tools; | X | ||||
| 4 | is able to express one’s mathematical ideas in an organised way both in written and oral forms; | X | ||||
| 5 | understands relations connecting substantial concepts and results; can switch from one viewpoint to another on mathematical objects (pictures, formulae, precise statements, heuristic trials, list of examples,...); | X | ||||
| 6 | has followed individually a guided learning strategy; has pursued steps toward the resolution of unfamiliar problems; | X | ||||
| 7 | has a theoretical and practical knowledge in computer science well adapted for learning a programming language; | X | ||||
| 8 | has investigated the relevance of modeling and using mathematical tools in natural sciences and in the professional life; is conscious about historical development of mathematical notions; | X | ||||
| 9 | has followed introduction to some mathematical or non-mathematical disciplines after one’s proper choice; had experience to learn selected subjects according to one’s proper arrangement; | X | ||||
| 10 | masters French language as well as other foreign languages, to a level sufficient to study or work abroad. | X | ||||
| Activities | Number | Period | Total Workload |
|---|---|---|---|
| Class Hours | 13 | 3 | 39 |
| Working Hours out of Class | 14 | 2 | 28 |
| Assignments | 5 | 2 | 10 |
| Presentation | 0 | 0 | 0 |
| Midterm Examinations (including preparation) | 1 | 5 | 5 |
| Project | 1 | 10 | 10 |
| Laboratory | 0 | 0 | 0 |
| Other Applications | 0 | 0 | 0 |
| Final Examinations (including preparation) | 0 | 0 | 0 |
| Quiz | 0 | 0 | 0 |
| Term Paper/ Project | 0 | 0 | 0 |
| Portfolio Study | 0 | 0 | 0 |
| Reports | 0 | 0 | 0 |
| Learning Diary | 0 | 0 | 0 |
| Thesis/ Project | 0 | 0 | 0 |
| Seminar | 0 | 0 | 0 |
| Other | 0 | 0 | 0 |
| Total Workload | 92 | ||
| Total Workload / 25 | 3.68 | ||
| Credits ECTS | 4 | ||