Course Details

Data Structures and Algorithms Using PYTHON

IT


Provider Name             :    GlobalOne Services

Course Type               :    Hybrid

Duration (Hrs)             :    90

Hours/day                 :    3

Training Type             :    Hybrid

Certification               :    yes

Orginal Price               :    15000/-

Discount Price             :    13500/-

No.of. vacancies         :    500

Last date to apply     :      2024-12-01


Full Information

Course Description

The DSA Using Python Course provides a solid foundation in data structures and algorithms using Python, making it ideal for beginners and intermediate programmers. This course covers essential topics like arrays, linked lists, trees, graphs, sorting algorithms, dynamic programming, and more. Python’s simplicity and readability make it an excellent language for understanding complex DSA concepts. Through hands-on coding exercises, real-world problem-solving, and project-based learning, students will build a strong skill set essential for software development, data science, and technical interviews. This course prepares students for a range of technical roles by honing their problem-solving skills and giving them a practical understanding of DSA in Python.

Topics to be covered

Module 1: Introduction to Data Structures and Algorithms
Overview of Data Structures and Their Importance
Understanding Time and Space Complexity (Big O Notation)
Introduction to Python for DSA (Data Types, Libraries, List Comprehensions)
Setting Up Python Environment (Jupyter, IDEs)

Module 2: Arrays and Lists
Basic Array Operations (Insertion, Deletion, Searching, Sorting)
Python List Operations and List Comprehensions
Solving Array-Based Problems and Using Python Libraries (NumPy)

Module 3: Linked Lists
Singly Linked List, Doubly Linked List, Circular Linked List
Linked List Operations (Insertion, Deletion, Traversal)
Problem Solving with Linked Lists in Python

Module 4: Stacks and Queues
Implementing Stacks and Queues Using Python Lists and Collections
Applications of Stack and Queue (Expression Evaluation, Parenthesis Matching)
Priority Queue and Deque

Module 5: Trees and Binary Trees
Tree Terminologies and Basic Concepts
Binary Tree and Binary Search Tree (BST) Implementation
Tree Traversals (Inorder, Preorder, Postorder, Level Order)
Problem Solving Using Trees and Binary Trees

Module 6: Advanced Trees
Balanced Trees (AVL Tree Basics)
Binary Heap and Priority Queue
Trie (Prefix Tree) and Its Applications
Segment Tree and Fenwick Tree for Range Queries

Module 7: Graphs
Graph Representation (Adjacency List, Adjacency Matrix)
Graph Traversal Algorithms (Breadth-First Search, Depth-First Search)
Shortest Path Algorithms (Dijkstra’s, Bellman-Ford)
Minimum Spanning Tree (Kruskal’s and Prim’s Algorithm)

Module 8: Hashing and Dictionaries
Introduction to Hashing and Hash Functions
Collision Resolution Techniques (Chaining, Open Addressing)
Implementing Hash Tables and Using Python Dictionaries
Solving Problems Using Hashing

Module 9: Sorting and Searching Algorithms
Sorting Algorithms (Bubble Sort, Insertion Sort, Merge Sort, Quick Sort)
Searching Algorithms (Linear Search, Binary Search)
Understanding and Applying Recursive Algorithms
Optimizing Search and Sort for Larger Data Sets

Module 10: Dynamic Programming and Greedy Algorithms
Introduction to Dynamic Programming (DP) Concepts
Solving Classic DP Problems (Knapsack, Longest Common Subsequence)
Greedy Algorithm Basics and Applications (Activity Selection, Huffman Coding)
Memoization and Bottom-Up Approaches

Module 11: Recursion and Backtracking
Basics of Recursion and Recursive Problem Solving
Divide and Conquer Strategy (Binary Search, Merge Sort)
Backtracking Problems (N-Queens, Sudoku Solver, Permutations)
Reducing Recursive Problems to Iterative Solutions

Module 12: Capstone Project
Real-World Problem Analysis and Solution Design
Building a Data Structure or Algorithm Project from Scratch
Code Optimization, Testing, and Debugging
Presenting and Documenting the Solution

Benefits of Course

The DSA Using Python Course empowers students with the core knowledge of data structures and algorithms essential for various fields, including software development, data science, and technical interviews. Python’s simplicity allows students to focus on mastering the logic behind data structures and algorithms, building strong problem-solving abilities. With hands-on coding exercises and projects, students will be equipped to tackle real-world challenges and develop optimized, efficient solutions. This course not only prepares students for technical interviews but also provides a solid programming foundation adaptable to other languages and technical roles.

Pre-Requirements

None