Python with DSA
Introduction to Python with DSA
- 1.294 students
- Last updated 25/03/2024
Descriptions
Introduction to Python Programming with Data Structures and Algorithms” is a comprehensive course designed to introduce participants to the Python programming language and fundamental concepts of data structures and algorithms. The course starts with an overview of Python basics, including variables, data types, control structures, and functions, providing a solid foundation for programming in Python. Participants will then delve into key data structures such as lists, tuples, dictionaries, sets, and explore algorithmic problem-solving techniques like sorting and searching algorithms. Additionally, the course covers object-oriented programming (OOP) principles in Python, advanced data structures like linked lists, trees, and graphs, algorithm analysis, and practical implementation through hands-on exercises and projects. By the end of the course, participants will have gained proficiency in Python programming, algorithmic thinking skills, and the ability to design and implement efficient software solutions using data structures and algorithms.
Throughout the course, participants will engage in interactive learning activities, coding challenges, and practical projects to reinforce their understanding and application of Python programming concepts and data structures. Whether you’re a beginner looking to start your programming journey or seeking to enhance your Python skills and dive deeper into algorithmic problem-solving, this course provides a structured and engaging learning experience to help you become proficient in Python programming and leverage data structures and algorithms effectively in your software development endeavors.
Key Points
- Participants will start by learning the basics of Python programming, including variables, data types, control structures (if-else, loops), functions, and modules.
- The course covers essential data structures such as lists, tuples, dictionaries, sets, stacks, queues, linked lists, trees, and graphs, exploring their implementation and operations.
- Participants will delve into algorithmic problem-solving techniques, covering sorting algorithms (e.g., bubble sort, merge sort), searching algorithms (e.g., linear search, binary search), and algorithm analysis.
- Understanding OOP concepts in Python, including classes, objects, inheritance, polymorphism, and encapsulation, for building modular and reusable code.
- Hands-on exercises, coding challenges, and projects will reinforce learning and help participants apply Python programming concepts, data structures, and algorithms in real-world scenarios.
- By the end of the course, participants will have gained proficiency in Python programming, algorithmic thinking skills, and practical experience necessary to pursue careers in software development, data science, machine learning, and related fields.
Course Lessons
- Overview of Python programming language.
- Installation and setup of Python environment.
- Basic syntax, variables, and data types in Python.
- Conditional statements (if-else), loops (for loop, while loop).
- Writing and calling functions in Python.
- Recursion and its applications.
- Lists, tuples, dictionaries, sets, and their operations.
- Working with multi-dimensional arrays (NumPy arrays).
- Understanding and implementing stacks and queues.
- Classes, objects, constructors, and methods in Python.
- Inheritance, polymorphism, and encapsulation concepts.
- Using OOP principles to design and implement Python programs.
- Linked lists (singly linked list, doubly linked list).
- Trees (binary tree, binary search tree) and their traversal techniques.
- Graphs (representation, traversal algorithms).
- Implementing sorting algorithms (bubble sort, selection sort, merge sort) in Python.
- Exploring searching algorithms (linear search, binary search) and their efficiency.
- Understanding time complexity and space complexity.
- Big O notation and asymptotic analysis of algorithms.
- Introduction to standard libraries (e.g., math, random, datetime).
- Working with external libraries and modules (e.g., NumPy, pandas).
- Solving algorithmic problems and coding challenges using Python.
- Implementing data structures and algorithms in Python.
- Working on mini-projects to apply learned concepts and showcase skills.
- Concluding the course with a comprehensive assessment.
- Earning a certificate upon successful completion of the course, demonstrating proficiency in Python programming and data structures/algorithms.
Instructor
Python Expert
This course includes:
- 40 hours on-demand Live Classes
- Full lifetime access
- Access on mobile, Tablet and Laptop
- 100% paid Internship Assurance
- Certificate of completion
