Course Objectives
1. What Does DSA with Python Training Cover?
DSA with Python training covers programming fundamentals, problem-solving techniques, and important data structures and algorithms using Python. Students learn topics like arrays, strings, linked lists, stacks, queues, trees, graphs, searching, sorting, recursion, and coding interview problems through practical coding sessions.
2. Who Can Join the DSA with Python Course?
This course is suitable for:
Students and freshers Beginners in programming Job seekers preparing for IT interviews Working professionals who want to improve coding skills Anyone interested in software development
3. Why Should You Learn DSA with Python?
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Learning DSA with Python helps improve coding, logical thinking, and problem-solving skills. It is very useful for software developer jobs, coding interviews, and technical rounds in IT companies.
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Python is easy to learn and widely used in the software industry, making it a great choice for learning DSA.
4. Is DSA with Python Good for Beginners?
Yes. The course starts from the basics and explains concepts in a simple and easy-to-understand way. Beginners can learn step by step with practical examples and coding exercises.
5. What Are the Main Topics Covered in DSA with Python?
The course covers:
Python basics Arrays and strings Searching and sorting Linked lists Stacks and queues Trees and graphs Recursion Hashing Dynamic programming basics Coding interview preparation
6. Why Choose EDUBRIGHTS for DSA with Python Training in Chennai?
EDUBRIGHTS provides beginner-friendly training with practical coding sessions, experienced trainers, and interview-focused learning.
Students receive:
- Real-time coding practice
- Hands-on assignments
- Simple explanations
- Flexible class timings
- Interview preparation support
- Career guidance
7. Does the Course Include Practical Coding Sessions?
Yes. The training includes practical coding exercises, real-time examples, and problem-solving sessions to help students improve their coding confidence.
Popular Techniques Covered in This Course
1.Core Python Programming
2.Object-Oriented Programming (OOP)
3.Web Frameworks
4.Data Structures & Algorithms
5.Database Management
6.Testing & Debugging
7.APIs and Integration
8.Advanced Python Concepts
9.Data Science & Machine Learning (Optional)
10.Version Control & Collaboration
Get Hands-on Knowledge about Real-Time Projects
Project 1
1 Student Record Management System
Develop a Python application using arrays, linked lists, and dictionaries to manage student records efficiently. Improve data organization and retrieval performance.
Project 2
2 Inventory Management System
Build an inventory management solution using stacks, queues, hashing, and searching algorithms. Optimize product tracking and stock management operations.
Project 3
3 Route Optimization Project
Implement graph algorithms to find the shortest path between multiple locations in a logistics or navigation system. Improve route planning and operational efficiency.
Project 4
4 Search Engine Simulation Project
Create a search application using hashing, trees, and efficient searching algorithms to retrieve information quickly. Enhance search accuracy and response time.
Project 5
5 Coding Challenge & Interview Project
Solve real-world algorithmic problems using recursion, dynamic programming, sorting, and graph algorithms. Build confidence for coding interviews and competitive programming.
Key Features
Edubrights offers Data Structure Algorithm with Python Training in virtual mode with expert trainers. Here are the key features,
40 Hours Course Duration
100% Job Oriented Training
Industry Expert Faculties
Free Demo Class Available
Completed 500+ Batches
Certification Guidance
Curriculum
Module 1: Introduction to DSA and Python
- Introduction to Data Structures and Algorithms
- Importance of DSA in software development
- Applications of DSA in real-world projects
- Why Python is preferred for DSA learning
- Installing Python and setting up the development environment
- Writing and running your first Python program
- Understanding Time Complexity and Space Complexity
- Introduction to Big O Notation
Module 2: Python Fundamentals for DSA
- Python syntax and coding basics
- Variables and data types
- Input and output operations
- Operators in Python
- Conditional statements
- Loops and iterations
- Functions and reusable code
- Introduction to recursion
Module 3: Arrays and Strings
- Understanding arrays and lists in Python
- Array traversal techniques
- Insertion and deletion operations
- Searching elements in arrays
- String manipulation techniques
- String methods and operations
- Solving array-based coding problems
- Interview questions on arrays and strings
Module 4: Searching and Sorting Algorithms
- Linear Search Algorithm
- Binary Search Algorithm
- Bubble Sort Technique
- Selection Sort Algorithm
- Insertion Sort Method
- Merge Sort Algorithm
- Quick Sort Technique
- Comparison of sorting algorithms
- Time complexity analysis
Module 5: Recursion and Backtracking
- Understanding recursive functions
- Recursive problem-solving methods
- Advantages of recursion
- Backtracking fundamentals
- Solving permutation and combination problems
- N-Queens problem
- Sudoku solver implementation
- Recursive interview problems
Module 6: Linked Lists
- Introduction to linked lists
- Singly linked list operations
- Doubly linked list concepts
- Circular linked list implementation
- Insertion and deletion in linked lists
- Traversing linked lists
- Reversing linked lists
- Applications of linked lists
Module 7: Stacks and Queues
- Introduction to stacks
- Stack implementation using Python
- Queue implementation techniques
- Circular queue concepts
- Priority queue basics
- Stack applications
- Queue applications
- Expression evaluation problems
- Balanced parentheses problems
Module 8: Hashing and Dictionaries
- Introduction to hashing concepts
- Hash tables and dictionaries in Python
- Collision handling techniques
- Sets and hash maps
- Frequency counting problems
- Hashing-based coding challenges
- Real-time applications of hashing
Module 9: Trees and Binary Search Trees
- Introduction to tree data structures
- Binary tree concepts
- Binary Search Tree implementation
- Tree traversal methods
- Inorder traversal
- Preorder traversal
- Postorder traversal
- Level order traversal
- Heap data structure
- Priority queues using heaps
Module 10: Graphs and Traversal Algorithms
- Introduction to graph data structures
- Graph representations
- Breadth First Search (BFS)
- Depth First Search (DFS)
- Shortest path algorithms
- Topological sorting
- Minimum spanning tree concepts
- Real-world graph applications
Module 11: Advanced Algorithms
- Greedy algorithms
- Divide and conquer techniques
- Dynamic programming basics
- Sliding window technique
- Two-pointer algorithm
- Bit manipulation concepts
- Optimization techniques
- Advanced problem-solving strategies
Module 12: Coding Interview Preparation
- Problem-solving approaches
- Coding interview techniques
- Competitive programming basics
- Mock coding interviews
- Solving real-time interview questions
- Resume preparation guidance
- GitHub profile optimization
- Coding platform practice sessions
Receive Training From Our Skilled and Effective Trainers
Experience in the Industry Gain knowledge from experts with practical Data Structure Algorithm with Python project experience in a variety of sectors.
Backgrounds at the Top Prominent corporations such as hcl, tcs , accenture and cognizant employ trainers.
Clear & Effective Teaching Excellent communication and real-world examples simplify complex subjects.
Hands-On Learning Focus Students can apply their abilities in real-world situations with the use of case studies and real-time projects.
Up-to-Date Knowledge Trainers stay current with the latest tools, techniques and best practices.
Succeed Our Resourceful Certification
Python certification is a formal credential that validates your proficiency and expertise in Python programming, demonstrating your ability to write efficient, clean, and scalable code
Course FAQs
1. What is Python?
Python is a high-level, interpreted, general-purpose programming language known for its readability, simplicity, and versatility across software development, data science, automation, and more.
2. What is the difference between global and local scope?
Variables defined inside a function have local scope and are accessible only within that function, whereas global variables are defined outside functions and accessible throughout the program.
3. What is an iterator in Python?
An iterator is an object that implements the iter() and next() methods, allowing traversal over all the values in a collection or sequence.
4. What is the __init__() function?
It is a special method in Python classes that initializes new objects, commonly used to assign initial values to object attributes.
5. When should you use lambda functions?
Lambda functions are anonymous, short functions used for simple operations, often as arguments to higher-order functions like map() or filter().
6. What are Python’s primary built-in data types?
They include text (str), numeric (int, float, complex), sequence (list, tuple, range), mapping (dict), set (set, frozenset), boolean (bool), and binary types (bytes, bytearray, memoryview).
7. What is inheritance in Python?
Inheritance allows a class (child) to acquire properties and methods from another class (parent), facilitating code reuse and hierarchical class structures.
8. What is PEP 8?
PEP 8 is the Python Enhancement Proposal that provides guidelines and best practices on how to write Python code for maximum readability.
9. How do you handle exceptions in Python?
Using try-except blocks to catch and manage errors gracefully, optionally handling multiple exceptions and creating custom exception classes.
10. What are Python libraries?
Collections of modules and packages that provide pre-built functionality, such as NumPy for numerical computing, Pandas for data analysis, and Matplotlib for visualization.
11. Is DSA useful beyond technical interviews?
Yes. DSA is essential for writing efficient, scalable, and maintainable software in real-world projects.
12. How does DSA improve programming skills?
It strengthens logical thinking, problem-solving ability, algorithm optimization, and software development expertise.
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