Data Structures in Python Practice Exam

Data Structures in Python Practice Exam

About the Data Structures in Python Practice Exam

Data Structures in Python covers the fundamental ways to organize and store data efficiently using built-in Python structures like lists, tuples, sets, and dictionaries. Understanding these data structures allows you to perform operations like data manipulation, searching, and sorting efficiently. With a strong grasp of these structures, you can solve complex problems, optimize algorithms, and improve the performance of your code in various applications such as web development, data analysis, and machine learning.

Skills Required

• Basic programming skills in Python, including syntax, variables, and functions.
• Understanding of algorithms, such as searching and sorting.
• Problem-solving skills to approach and solve challenges efficiently.
• Basic understanding of mathematical concepts like time and space complexity (Big O notation).
• Logical thinking for organizing and manipulating data for different tasks.

Knowledge Gained

• Proficiency in using Python’s built-in data structures like lists, tuples, sets, and dictionaries.
• Ability to select and implement the appropriate data structure for solving specific problems.
• Understanding of how data structures impact the performance and efficiency of algorithms.
• Skills in optimizing code by applying the right data structures to minimize time and space complexity.
• Experience in manipulating and organizing data for a variety of applications, from basic programs to more complex projects.
• Knowledge of advanced data structures, such as stacks, queues, linked lists, and trees.

Who should take the Exam?

• Aspiring Python developers looking to strengthen their understanding of data structures.
• Computer science students who want to test their knowledge of data structures and algorithms in Python.
• Software engineers aiming to improve their coding efficiency and problem-solving abilities.
• Data scientists and analysts who need a strong grasp of data structures for data manipulation and analysis.
• Beginners in programming who want to solidify their foundation in data structures.
• Professionals preparing for coding interviews that require knowledge of data structures and algorithm optimization.

Course Outline

Arrays in Python

• Definition
• Creating and Displaying 1D Arrays
• Accessing 1D Arrays
• Searching in 1D Arrays
• Insertion in 1D Arrays
• Deletion in 1D Arrays
• Updating in 1D Arrays
• Accessing 2D Arrays
• Insertion Operation in 2D Arrays
• Deletion Operation in 2D Arrays
• Update Operation in 2D Arrays

Lists, Tuples, Sets, and Dictionaries in Python

• Accessing Elements & Searching Element in a List
• Working with Operators on Lists
• Indexing and Slicing in Lists
• Working with List Methods
• Append()
• Clear()
• count()
• extend()
• index()
• insert()
• pop()
• remove()
• reverse()
• sort()
• List Comprehension
• Finding Maximum and Minimum Element in a List
• Tuples
• Tuple Indexing and Slicing
• Manipulating Tuples
• Unpacking Tuples
• Basics of Dictionary
• Accessing dictionary elements
• Working with dictionary
• Understanding Sets in Python

Recursion

• Functions in Python
• Example Program1 on Functions
• Example Program2 on Functions
• Example Program3 on Functions
• Recursion

Linked Lists

• Basics of Linked Lists
• Inserting an Element in a Linked List
• Searching an Element in a Linked List
• Finding Middle Element in a Linked List
• Checking Whether Two Given Linked Lists are Identical or Not
• Finding Maximum Value in a Linked List
• Deleting the Linked List

Stacks

• Understanding Stacks
• Implementing Stacks in Python
• Implementing Stacks Using Lists with Built-in Methods in Python
• Implementing Stacks Using Collections-dequeue in Python
• Implementing Stacks Using Queue-LifoQueue in Python
• Linked List Implementation of Stacks in Python
• Stack Application: Balanced Parenthesis
• Using Stacks for Checking Balanced Parenthesis

Queues

• Understanding Queues
• Implementing Queues Using Lists with Built-in Methods in Python
• Implementing Queues Using Collections-dequeue in Python
• Implementing Queues Using Queue Module in Python
• Implementing Queues Using LinkedLists
• Circular Queues

Trees

• Tree Terminology
• Defining Binary Tree and Complete Binary Tree
• Representation of a Binary Tree
• Binary Tree Traversals
• How to Implement Inorder Traversal in Python?
• How to Implement Pre-order Traversal in Python?
• How to Implement Post-order Traversal in Python?
• How to Implement Height of a Binary Tree in Python?
• Sum of Elements in a Binary Tree

Binary Search Trees

• Definition of BST with Example
• Search Operation in BST
• Inserting a Node in BST
• Creating a BST

Graphs

• Basics of Graphs
• Adjacency Matrix Representation
• Adjacency List Representation