This course will help you master essential data structures in Python, enabling you to write efficient code, optimize memory, and solve complex problems. By the end, you’ll be proficient in implementing arrays, linked lists, stacks, queues, trees, and graphs, along with recursion, searching, and sorting techniques.
You’ll start with fundamental data structures like arrays, lists, tuples, sets, and dictionaries, learning operations such as insertion, deletion, and searching. Next, you’ll explore dynamic structures like linked lists, stacks, and queues, followed by recursion for problem-solving.
The course then covers hierarchical structures like binary trees and binary search trees, focusing on traversal and search optimization. Finally, you’ll dive into graphs, learning representation techniques for network-based data structures.
Ideal for students and aspiring developers, this course strengthens problem-solving skills. A basic understanding of Python is recommended as the course progresses from fundamentals to advanced topics.
Overview
Syllabus
- Arrays in Python
- In this module, we will explore the fundamentals of arrays, including their creation, manipulation, and applications. Starting with 1D arrays, we will cover essential operations such as searching, insertion, deletion, and updating. Then, we will progress to 2D arrays, learning how to access, insert, delete, and update elements, equipping you with the skills to handle data in Python effectively.
- Lists, Tuples, Sets, and Dictionaries in Python
- In this module, we will dive into Python's versatile data structures: lists, tuples, sets, and dictionaries. You will learn to perform operations like accessing, modifying, and extending lists, as well as unpacking tuples and managing dictionary key-value pairs. This section also introduces set operations, preparing you for efficient data storage and retrieval techniques.
- Recursion
- In this module, we will cover the essentials of recursion, starting with function basics and progressively building towards recursive solutions. You will learn how to design, implement, and debug recursive algorithms, gaining insights into their utility in solving problems like factorial computation and tree traversal.
- Linked Lists
- In this module, we will delve into linked lists, a dynamic data structure suited for efficient memory usage. You will learn to perform operations such as insertion, deletion, and searching, along with advanced techniques like identifying the middle element and comparing linked lists. This module concludes with memory management techniques like deleting a linked list.
- Stacks
- In this module, we will explore stacks, a fundamental data structure. You will learn various implementation methods using Python's list, collections, and queue modules. Additionally, you will apply stack operations to solve problems such as ensuring balanced parentheses, preparing you for practical programming challenges.
- Queues
- In this module, we will study queues and their variants, including circular queues. You will learn how to implement queue operations using Python's built-in methods and modules. The focus will also include optimizing space and time complexities for sequential data management.
- Trees
- In this module, we will explore tree structures, starting with basic terminology and progressing to binary trees. You will learn traversal techniques and implement operations to compute height and sum elements. This module lays the groundwork for understanding hierarchical data organization.
- Binary Search Trees
- In this module, we will focus on binary search trees, a specialized tree structure optimized for searching and data organization. You will learn how to create, search, and insert nodes into a BST, preparing you for applications that require fast and ordered data handling.
- Graphs
- In this module, we will introduce graphs, one of the most versatile data structures in computer science. You will learn to represent graphs using adjacency matrices and lists, equipping you with the tools to understand and implement graph-based algorithms for real-world problems.
Taught by
Packt - Course Instructors
