Hands-On Data Structures And Algorithms With Python: Learn by Doing with Pictorial Representations,
- berrocondesk1975
- Aug 16, 2023
- 5 min read
Dr. Basant Agarwal works as an Assistant Professor at the Indian Institute of Information Technology Kota. He holds a PhD and MTech from the Department of Computer Science and Engineering, Malaviya National Institute of Technology, Jaipur, India. Basant has 10+ years of experience in academia and research, and he was awarded the prestigious PostDoc Fellowship by the European Research Consortium for Informatics and Mathematics through the Alain Bensoussan Fellowship Programme. He has been teaching a course on data structures and algorithms to undergraduates for a while now and is highly experienced in working with Python for developing real-world applications. His research interests include NLP, machine learning, and deep learning.
Choosing the right data structure is pivotal to optimizing the performance and scalability of applications. This new edition of Hands-On Data Structures and Algorithms with Python will expand your understanding of key structures, including stacks, queues, and lists, and also show you how to apply priority queues and heaps in applications. You'll learn how to analyze and compare Python algorithms, and understand which algorithms should be used for a problem based on running time and computational complexity. You will also become confident organizing your code in a manageable, consistent, and scalable way, which will boost your productivity as a Python developer.
Hands-On Data Structures And Algorithms With Python
Data structures allow you to store and organize data efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential Python data structures and the most common algorithms for building easy and maintainable applications.
This book helps you to understand the power of linked lists, double linked lists, and circular linked lists. You will learn to create complex data structures, such as graphs, stacks, and queues. As you make your way through the chapters, you will explore the application of binary searches and binary search trees, along with learning common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. In the concluding chapters, you will get to grips with organizing your code in a manageable, consistent, and extendable way. You will also study how to bubble sort, selection sort, insertion sort, and merge sort algorithms in detail.
We just released a course on the freeCodeCamp YouTube channel that is a beginner-friendly introduction to common data structures (linked lists, stacks, queues, graphs) and algorithms (search, sorting, recursion, dynamic programming) in Python.
This book is for developers and programmers who are interested in learning about data structures and algorithms in Python to write complex, flexible programs. Basic Python programming knowledge is expected.
In this course you will learn data structures and algorithms by solving 80+ practice problems. You will begin each course by learning to solve defined problems related to a particular data structure and algorithm. By the end of each course, you would be able to evaluate and assess different data structures and algorithms for any open-ended problem and implement a solution based on your design choices.
Learn different data structures that can be used to store data. Implement different methods used to manipulate these data structures and examine the efficiency. Understand the advantages and applications of different data structures. Learn how to approach open ended problems (either in interview or real-world) and select appropriate data structures based on requirements.
Learn and implement basic algorithms such as searching and sorting on different data structures and examine the efficiency of these algorithms. Use recursion to implement these algorithms and then learn how some of these algorithms can be implemented without recursion. Practice selecting and modifying these algorithms for a variety of interview problems.
Whether you want to be a web developer, a machine learning engineer, or a data scientist, having a deep understanding of Data Structures and Algorithms is essential to acing job interviews and becoming a successful software engineer. As Linus Torvalds famously said, "Bad programmers worry about the code. Good programmers worry about data structures and their relationships".
While this course is not designed to prepare you for a specific job, after completing this program, you will have had extensive practice solving data structures and algorithm problems to help you prepare for the data structures and algorithms part of coding interviews.
If you are looking to improve your skills in data structures and algorithms -- to prepare for the technical portion of job interviews, to improve your software engineering skills, etc. -- then this Nanodegree program will provide you with extensive practice with defined and open-ended problems so that you learn how to implement the appropriate solution based on your design choices.
A data structure is a named location that can be used to store and organize data. And, an algorithm is a collection of steps to solve a particular problem. Learning data structures and algorithms allow us to write efficient and optimized computer programs.
Learners will solve data-structure problems by analyzing and designing algorithms for searching, sorting, and indexing; creating trees and graphs; and addressing intractability. Courses also include conceptual algorithm design problems as well as opportunities to program data-structures/algorithms in the python programming language.
Basic algorithms on tree data structures, binary search trees, self-balancing trees, graph data structures and basic traversal algorithms on graphs. This course also covers advanced topics such as kd-trees for spatial data and algorithms for spatial data.
This course covers basic algorithm design techniques such as divide and conquer, dynamic programming, and greedy algorithms. It concludes with a brief introduction to intractability (NP-completeness) and using linear/integer programming solvers for solving optimization problems. We will also cover some advanced topics in data structures.
Courses do not have to be taken a specific order, though it's recommended that learners follow the sequence of courses if they have no previous experience with data structures or algorithm analysis and design.
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Choosing the right data structure is pivotal to optimizing the performance and scalability of applications. This new edition of Hands-On Data Structures and Algorithms with Python will expand your understanding of key structures, including stacks, queues, and lists, and also show you how to apply priority queues and heaps in applications....
This book explains the concepts and techniques required to write programs that can handle large amounts of data efficiently. Project-oriented and classroom-tested, the book presents a number of important algorithms supported by examples that bring meaning to the problems faced by computer programmers. The idea of computational complexity ...
Based on the authors' market leading data structures books in Java and C++, this textbook offers a comprehensive, definitive introduction to data structures in Python by respected authors. Data Structures and Algorithms in Python is the first mainstream object-oriented book available for the Python data structures course. Designed ...
As an experienced JavaScript developer moving to server-side programming, you need to implement classic data structures and algorithms associated with conventional object-oriented languages like C# and Java. This practical guide shows you how to work hands-on with a variety of storage mechanisms - including linked lists, stacks, queues, a... 2ff7e9595c
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