Data Structures and Algorithm in Python

About this course

Description
Welcome to the Data Structures and Algorithms in Python course, expertly designed to give you a robust understanding of essential concepts for problem-solving and technical interviews. Through engaging lessons and practical challenges, you will master the core building blocks of efficient coding and computational thinking.

What You Will Achieve

Master the Fundamentals: Learn about foundational data structures such as arrays, lists, stacks, queues, and trees, along with algorithm basics like searching, sorting, and recursion.
Develop Problem-Solving Skills: Tackle real-world coding problems to enhance your ability to devise efficient algorithms and apply data structures effectively.
Optimize Code: Understand time and space complexity to write optimized and scalable code.
Grasp Advanced Concepts: Dive into advanced topics like graph algorithms, dynamic programming, and greedy methods, expanding your toolkit for complex problems.
Prepare for Interviews: Build the confidence to solve coding interview challenges using Python with clarity and precision.

What You’ll Learn

Introduction to Data Structures: Understand the role and importance of data structures in programming. Learn how to choose the right one for specific scenarios.
Algorithms Overview: Get an introduction to algorithm design, complexity analysis, and key paradigms like divide and conquer.
Core Data Structures: Explore arrays, linked lists, stacks, queues, hash tables, and trees with hands-on implementation in Python.
Searching and Sorting: Implement fundamental algorithms like binary search, quicksort, mergesort, and more.
Dynamic Programming: Learn to solve complex problems efficiently by breaking them into simpler sub-problems.
Graph Algorithms: Explore graph traversal techniques like BFS and DFS, shortest paths, and minimum spanning trees.
Problem-Solving Practice: Work on curated coding challenges to solidify your understanding and improve your speed.

Who This Course Is For

Beginners in Programming: Individuals just starting with Python and eager to learn essential concepts in algorithms and data structures.
Computer Science Students: Undergraduates seeking to strengthen their understanding of core CS concepts and ace academic exams.
Competitive Programmers: Coders aiming to excel in competitive coding contests by mastering efficient algorithms and Python tricks.
Job Seekers: Aspiring software engineers preparing for technical interviews at top companies.
Experienced Programmers: Developers wanting to brush up on data structures and algorithms to write more optimized and scalable code.

Our Instructor Mr. Prashant Sir

Experienced instructor with a deep understanding of programming and DSA oin python. He Has worked extensively in both academic and corporate settings, delivering high-quality training sessions. Specializes in simplifying complex logic and problem-solving techniques for students. Dedicated to helping learners grasp core programming concepts with ease. Proficient in guiding students through competitive programming and technical interview preparation.

Resources

For more such resources and Practise DSA questions, do visit Data Structures and Algorithms Interview Preparation Codes By Career Credentials and Primitive data types Interview Preparation Codes By Career Credentials.

Prepare yourself to delve into our resource portal, Prepcrazy featuring programming notes, informative books, interview question sets, coding platforms, and much more. Feel free to explore it whenever you can.

Course content

8 sections • 50 lectures

Create queue with size limit
Visual representation of queue
Queue data structure introduction
Create queue without size limit

Stack algorithm
Visual representation of stack
Stack creation without size limit
Introduction of stack data structure
WAP to reverse the string using stack
stack implementation with size limit

Bubble sort for decending order
Introduction to Bubble Sort
Bubble sort coding implementation
Bubble sort pseudocode and example

Introduction to Insertion sort
Insertion sort pseudocode and example
Insertion sort coding implementation - 1
Insertion sort coding implementation - 2

Introduction to Selection sort
Selection sort pseudocode and example
Selection sort coding implementation

Merge sort coding implementation
Introduction of sorting algorithm
Merge sort example and explanation
Merge sort coding example implementation
Introduction to Merge Sort

Types of data structure
What is exponential time?
Example of time complexity
What is linearithmic time O(n log n)
Execution of linear search practical
Algorithm and pseudocode of linear search
Algorithm and Pseudocode of binary search
Check username exist or not using linear search
WAP to search lesson from book by using Binary Search
Check book is exist or not using linear search algorithm
What is quadratic time?
Basics of data structure
What is linear time O(n)
Example of binary search
List data structure
What is time complexity?
What is constant time O(1)
What is best case scenario ?
Time complexity different notation
What is algorithm?
Examples of algorithm
Introduction of best case average case and worst case
What is Data Structure?
Importance of Data Structure

My journey filled with intellectual curiosity, innovation, and the pursuit of unlocking the potential of technology. As a computer science aspirant, you embark on a path that leads to a world where algorithms shape our lives, software powers our devices, and digital solutions revolutionize industries. my passion for this field reflects a desire to explore the depths of computational theory, problem-solving, and creative thinking. At its core, computer science is not just about programming and coding; it's about understanding complex systems, analyzing data, and designing efficient solutions to real-world challenges. As you delve into the realm of computer science, you'll develop a strong foundation in various programming languages, data structures, and algorithms, enabling you to craft elegant and robust software applications.