AI231
ALGORITHMS AND DATA STRUCTURES
- Course Code
- AI231
- Semester
- Third Term (Fall)
- Theory+Practice
- 3 + 1
- ECTS
- 5
| Course Type | Compulsory Course | ||||||||||||||||||||||||||||||
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| Course Level | Bachelor's Degree | ||||||||||||||||||||||||||||||
| Year of Study | 2 | ||||||||||||||||||||||||||||||
| Semester | Third Term (Fall) | ||||||||||||||||||||||||||||||
| ECTS | 5 | ||||||||||||||||||||||||||||||
| Name of Lecturer(s) | - | ||||||||||||||||||||||||||||||
| Learning Outcomes |
At the end of this course, the students;
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| Mode of Delivery | Face to face | ||||||||||||||||||||||||||||||
| Prerequisites | Yes(AI102) | ||||||||||||||||||||||||||||||
| Recommended Optional Programme Components | |||||||||||||||||||||||||||||||
| Course Description | Introduction to data abstraction and structures: linked lists, stacks, queues, hash tables, trees, graphs. Introduction to algorithms: complexity, recursion, dynamic programming, searching and sorting algorithms. Applications in AI: State space representation, Knowledge representation structures, Memory-efficient data structures for ML. | ||||||||||||||||||||||||||||||
| Course Contents |
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| Recommended or Required Reading | * Data Structures and Algorithms in Python - Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser * Problem Solving with Algorithms and Data Structures Using Python - Bradley N. Miller, David L. Ranum * Python Data Structures and Algorithms - Benjamin Baka * Artificial Intelligence: A Modern Approach - Stuart Russell, Peter Norvig * Grokking Algorithms: An Illustrated Guide for Programmers and Other Curious People - Aditya Bhargava | ||||||||||||||||||||||||||||||
| Planned Learning Activities and Teaching Methods |
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| Assessment Methods and Criteria |
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| Language of Instruction | Turkish | ||||||||||||||||||||||||||||||
| Work Placement(s) | No |
Programme Qualifications / Learning Outcomes
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