1668A, 14th Main Rd, Sector 7, HSR Layout, Bengaluru, Karnataka 560102
+91 99459 30733 (9am - 6pm IST, Tuesday - Sunday)
Welcome to the Python Data Structures and Algorithms Course, an essential stepping stone for anyone aiming to become a proficient programmer. In today's tech-driven world, understanding how to effectively manage and manipulate data is crucial. This course is designed to equip you with the skills to solve complex problems efficiently, giving you a competitive edge in the field of software development.
Throughout this course, you will dive into the core concepts of data structures and algorithms, learning how to analyze the performance of your code and optimize it for real-world applications. From understanding the basics of arrays and linked lists to mastering advanced topics like binary trees and priority queues, this curriculum covers a wide spectrum of fundamental techniques. By the end of this journey, you will not only be able to write cleaner, more efficient code but also gain the confidence to tackle challenging coding interviews and projects.
By enrolling in this course, you are investing in your future as a capable and resourceful programmer. With a blend of theoretical knowledge and practical exercises, you will develop a deep understanding of how to apply these concepts in various scenarios. Whether you're a student, a professional, or a coding enthusiast, this course will help you build a strong foundation in Python, preparing you for advanced studies and career opportunities in the ever-evolving tech industry.
Join us and take the first step towards becoming a master of data structures and algorithms!
1. Introduction and Complexity Analysis:
- Learn the basics of algorithm efficiency.
- Understand time complexity using Big O notation.
- Explore space complexity and its significance.
- Introduction to arrays and their basic operations.
2. Arrays and Sorting:
- Master array manipulation techniques.
- Learn the sliding window technique for subarray problems.
- Understand the two-pointer method.
- Explore various sorting algorithms and their applications.
3. Hashmaps and Binary Search:
- Introduction to hashmaps and their usage.
- Understand the concept of monotonic functions.
- Learn binary search for efficient element retrieval in sorted arrays.
4. Linked Lists:
- Understand the structure and operations of linked lists.
- Learn the hare and tortoise algorithm for cycle detection.
5. Queues and Stacks:
- Implement and utilize queues in different scenarios.
- Learn about stacks and their applications in problem-solving.
6. Recursion and Backtracking:
- Develop a recursive thinking approach.
- Visualize problems using recursion trees.
- Understand backtracking techniques for solving complex problems.
7. Priority Queues and Heaps:
- Learn about priority queues and their implementations.
- Understand heaps and their role in efficient data handling.
8 .Binary Trees and BST:
- Explore the structure and operations of binary trees.
- Learn about binary search trees (BSTs) and their properties.
- Master tree traversal methods: inorder, preorder, and postorder.