Sorting and Searching - Concepts, Algorithms and Python Code from Udemy

Sorting and Searching are fundamental operations frequently used by Computers. Whenever we log in to the system, the user enters the credentials. The system searches to the authorization database and validates to allow the user to enter the system. Searching becomes efficient when the data is in sorted form. A well-sorted Pharmaceutical Shop is an example of a sorted dataset. When a customer gives the prescription sheet, the pharmacist searches in the shop for the required medicine easily as the medicines are in sorted order. Sorting has been studied extensively by researchers for a long time in the domain of Algorithms and Data Structures. In this course, we teach two important searching algorithms, Linear Search and Binary Search. Binary Search leverages the fact that the data are in sorted order. While Linear Search scans the data linearly from one end to the other in O(n) time, Binary Search uses an interesting technique and accomplishes the task in Olog2n) time. We teach the simple and straightforward sorting algorithms, Bubble Sort, Quick Sort, Insertion Sort, and Selection Sort. For each of the algorithms we teach in the following steps:

1. Concepts and Principles

2. Illustration with a dataset

3. Algorithm

4. Python Program

5. Analysis of Algorithms on the Computational Complexity

We then teach interesting Sorting algorithms Radix Sort and Shell's Diminishing Increment Sort. At the end of the course, the student will be able to appreciate the searching and sorting algorithms and gain hands-on experience on Python Programs for Sorting and Searching.

What's inside

Learning objectives

Searching algorithms
Sorting algorithms

Python code for sorting and searching algorithms
Complexity analysis

Searching algorithms
Sorting algorithms
Python code for sorting and searching algorithms
Complexity analysis

Syllabus

Introduction

Algorithms and Complexity Analysis

Linear Search Alogrithm - Principles, Concepts, Algorithms, Python Program and Complexity Analysis

Linear Search - Concepts, principles, algorithms and Python Program

Linear Search Analysis of Algorithms

Binary Search

Complexity Analysis of Binary Search

Bubble Sorting

Bubble Sort Complexity Analysis

Insertion Sort

Comparision between Bubble Sort and Insertion Sort

Insertion Sort Analysis of Algorithms

Selection Sort

Compare Selection Sort and Bubble Sort

Selection Sort Complexity Analysis

Shells Diminishing Increment Sort

Radix Sort - Concepts, Principles and Algorithm

Python Program for Radix Sort

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Explores searching and sorting algorithms, which are essential for efficient data processing and retrieval in various applications

Teaches complexity analysis, which is crucial for evaluating the performance and scalability of algorithms in different scenarios

Includes Python implementations of each algorithm, providing hands-on experience and practical application of theoretical concepts

Covers both basic sorting algorithms like Bubble Sort and Insertion Sort, as well as more advanced algorithms like Quick Sort and Radix Sort

Reviews summary

Fundamentals of sorting and searching in python

Según los estudiantes, este curso proporciona una sólida introducción a los algoritmos fundamentales de ordenación y búsqueda. Muchos encuentran que las explicaciones de los conceptos son claras y bien presentadas, especialmente para principiantes. Las implementaciones en código Python son destacadas como un punto fuerte, ayudando a visualizar y aplicar los algoritmos. Si bien cubre los algoritmos esenciales y su análisis de complejidad, algunos comentarios sugieren que el curso se centra principalmente en lo básico y podría carecer de la profundidad necesaria para temas más avanzados o una preparación exhaustiva para entrevistas técnicas. En general, es visto como un excelente punto de partida para quienes se inician en el tema.

Algorithm efficiency is adequately covered.

"Complexity Analysis is well explained."

"Analysis of Algorithms on the Computational Complexity is included."

"The time and space complexity is covered for each algorithm."

Provides a solid foundation in key algorithms.

"Gives a good foundation on sorting and searching algorithms."

"Covers all necessary concepts well for a beginner."

"Provides a good introduction to fundamental algorithms."

Well-suited for those new to algorithms.

"This course is good for beginners who want to understand Sorting and Searching Algorithms."

"A great course for beginners."

"Perfect course to start with Sorting and Searching Algorithms."

Helpful Python code examples are provided.

"The python code examples provided are very helpful for understanding the implementation."

"The use of Python to demonstrate the algorithms is very practical."

"Every single topic is explained with examples and codes."

"The implementations in Python make it easier to grasp the concepts."

Concepts are explained clearly and logically.

"The concepts are well explained and easy to understand."

"Excellent course, very clear explanation of algorithms."

"The explanation was very clear and concise."

"Instructor explains things very clearly."

"Every single topic is explained with examples and codes."

May not be sufficient for advanced topics.

"Could be more in-depth for advanced learners."

"It's a basic course, not enough for coding interviews."

"Primarily covers introductory material."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Sorting and Searching - Concepts, Algorithms and Python Code with these activities:

Review Basic Python Syntax

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Reinforce your understanding of Python syntax, which is essential for implementing the sorting and searching algorithms covered in the course.

Browse courses on Python Syntax

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Review data types, control flow, and functions in Python.
Practice writing simple Python programs.

Review 'Grokking Algorithms'

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Solidify your understanding of algorithms with a beginner-friendly guide that explains concepts visually.

View Grokking Algorithms, Second Edition on Amazon

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Read the chapters on sorting and searching algorithms.
Work through the examples and exercises in the book.

Implement Sorting Algorithms from Scratch

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Reinforce your understanding of sorting algorithms by implementing them yourself without using built-in Python functions.

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Choose a sorting algorithm (e.g., bubble sort, insertion sort).
Write Python code to implement the algorithm.
Test your implementation with various datasets.

Four other activities

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Create a Visual Comparison of Sorting Algorithms

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Deepen your understanding by creating a visual representation (e.g., a chart or animation) comparing the performance of different sorting algorithms.

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Select a few sorting algorithms to compare.
Generate data to visualize their performance (e.g., time complexity).
Create a chart or animation to present the comparison.

Build a Searchable Data Structure

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Apply your knowledge by building a data structure (e.g., a binary search tree) that allows for efficient searching.

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Choose a data structure suitable for searching.
Implement the data structure in Python.
Implement search functionality for the data structure.
Test the performance of your search implementation.

Review 'Introduction to Algorithms' (CLRS)

Show steps

Deepen your understanding of algorithms with a comprehensive textbook that covers theoretical aspects.

View Introduction to Algorithms, fourth edition on Amazon

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Read the relevant chapters on sorting and searching.
Work through the exercises to test your understanding.

Contribute to an Open Source Sorting Library

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Enhance your skills by contributing to an open-source project that involves sorting algorithms.

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Find an open-source project related to sorting algorithms.
Identify a bug or feature to work on.
Contribute your code to the project.

Career center

Learners who complete Sorting and Searching - Concepts, Algorithms and Python Code will develop knowledge and skills that may be useful to these careers:

Software Engineer

A software engineer designs, develops, tests, and maintains software applications. This course helps build a foundation in fundamental algorithms, which are crucial for any software engineer. Understanding sorting and searching algorithms allows you to write efficient and optimized code. This course, in particular, helps you learn several important sorting algorithms such as Bubble Sort, Quick Sort, and Insertion Sort along with searching algorithms such as Linear Search and Binary Search. You also learn how to analyze the runtime complexity of different algorithms. With the hands-on experience of implementing the algorithms in Python gained from this course, you will be well-prepared to tackle complex software engineering challenges.

See salaries and explore the career path for Software Engineer

Algorithm Developer

An algorithm developer researches, designs, and implements algorithms for various applications, often requiring an advanced degree. This course provides a deep dive into sorting and searching algorithms, which are fundamental building blocks for more complex algorithms. This course provides the concepts and principles behind important algorithms like Bubble Sort, Quick Sort, Insertion Sort, and Selection Sort. If you want to become an Algorithm Developer, you will also benefit from the Python implementations and computational complexity analysis covered in this course.

See salaries and explore the career path for Algorithm Developer

Research and Development Scientist

Research and development scientists conduct research and develop new technologies. This usually requires a master's degree or a doctorate. This course helps build a foundation for algorithm design and analysis, which are crucial for developing innovative solutions in various fields. The course focuses on important searching algorithms, Linear Search and Binary Search. The concepts, principles, and Python implementations of sorting and searching algorithms covered in this course, as well as the complexity analysis, will equip you with the skills to tackle complex research challenges.

See salaries and explore the career path for Research and Development Scientist

Data Scientist

Data scientists use statistical methods and algorithms to analyze large datasets and extract meaningful insights. This course helps build a foundation for efficiently handling and processing data, a core component of a data scientist's work. An understanding of sorting and searching algorithms becomes essential when dealing with large datasets. This course teaches you the important searching algorithms, Linear Search and Binary Search. In particular, the course covers how to implement these algorithms in Python, a commonly used language in data science. With the complexity analysis taught in this course, you can also evaluate the performance of different algorithms and choose the most suitable one for a given task.

See salaries and explore the career path for Data Scientist

Full-Stack Developer

A Full Stack Developer works on both the front-end and back-end of web applications. This course helps build a foundation in algorithms and data structures, which are crucial for developing efficient and scalable web applications. This course covers important searching algorithms, Linear Search and Binary Search. With the hands-on experience of implementing these algorithms in Python, which this course provides, you will be better equipped to select and implement the right algorithms for your web application projects.

See salaries and explore the career path for Full-Stack Developer

Machine Learning Engineer

A Machine Learning Engineer develops and deploys machine learning models. This often requires knowledge of algorithms and data structures. This course helps build a foundation by covering essential sorting and searching algorithms, which are frequently used in data preprocessing and feature engineering. The course teaches you how to implement the covered algorithms in Python, which will likely prepare you for working with machine-learning libraries. Knowledge of different sorting algorithms and their performance implications, as taught in this course, will enable you to optimize data handling within machine learning pipelines.

See salaries and explore the career path for Machine Learning Engineer

Game Developer

Game developers create video games for computers, consoles, and mobile devices. This course helps build a foundation in optimizing game performance, where sorting and searching algorithms are frequently used for tasks such as managing game objects, collision detection, and artificial intelligence. The course covers important searching algorithms, Linear Search and Binary Search. The complexity analysis of algorithms covered in this course help optimize the performance of games.

See salaries and explore the career path for Game Developer

Data Analyst

Data analysts examine data to identify trends, answer questions, and make recommendations. This course helps build a foundation for data manipulation and analysis, as efficient sorting and searching are core components of data processing. The course teaches you important searching algorithms, Linear Search and Binary Search. In particular, the Python implementations and complexity analysis of sorting and searching algorithms covered in this course will enable you to process and analyze data more efficiently.

See salaries and explore the career path for Data Analyst

Bioinformatician

Bioinformaticians analyze biological data using computational tools and techniques. This often requires an advanced degree. This course helps build a foundation for processing and analyzing large biological datasets, where sorting and searching algorithms are used for sequence alignment, phylogenetic analysis, and genomic data analysis. This course teaches you important searching algorithms, Linear Search and Binary Search. The Python implementations and complexity analysis of sorting and searching algorithms covered in the course will enable you to process and analyze biological data more efficiently.

See salaries and explore the career path for Bioinformatician

Database Administrator

Database administrators are responsible for maintaining and optimizing databases, and ensuring data is readily available. This course may be useful, as searching and sorting algorithms are crucial components of database systems. The course provides a solid foundation in these algorithms, specifically addressing searching algorithms, Linear Search and Binary Search. Understanding the principles, implementation in Python, and complexity analysis covered in the course may assist Database Administrators in optimizing database queries and improving performance.

See salaries and explore the career path for Database Administrator

Cybersecurity Analyst

Cybersecurity analysts protect computer systems and networks from cyber threats. This course may be useful because an understanding of algorithms helps in analyzing and detecting malicious code, intrusion detection, and data encryption. The course covers important searching algorithms, Linear Search and Binary Search. You may learn to analyze the efficiency of different encryption algorithms and develop secure coding practices by understanding the concepts, principles, and complexity analysis of sorting and searching algorithms.

See salaries and explore the career path for Cybersecurity Analyst

Quality Assurance Engineer

Quality assurance engineers are responsible for ensuring the quality of software products. This course may be useful because a strong understanding of algorithms allows for better test case design and performance evaluation. The course teaches several algorithms which can lead to a better understanding of software processes. This course will help you design thorough test cases and identify potential performance bottlenecks by understanding complexity analysis.

See salaries and explore the career path for Quality Assurance Engineer

Data Architect

Data architects design and build data management systems for organizations. This course may be useful because a strong understanding of algorithms allows for efficient data storage, retrieval, and processing. This course covers important searching algorithms, Linear Search and Binary Search. By understanding the concepts, principles, and complexity analysis of sorting and searching algorithms, you'll be able to design scalable and efficient data management solutions.

See salaries and explore the career path for Data Architect

Product Manager

Product managers guide the development and launch of new products. This course may be useful as it helps build a foundation for understanding the technical aspects of software development and algorithm design, which can inform product decisions. The course covers important searching algorithms, Linear Search and Binary Search. Understanding the concepts and principles behind sorting and searching algorithms, as well as the complexity analysis, can help you communicate effectively with engineering teams and make informed product decisions.

See salaries and explore the career path for Product Manager

Financial Analyst

Financial analysts provide guidance to businesses and individuals making investment decisions. This course may be useful because sorting and searching algorithms can be applied to financial data for tasks such as portfolio optimization and fraud detection. This course teaches you how to implement algorithms in Python, and the complexity analysis provided in the course may allow you to analyze financial data more efficiently.

See salaries and explore the career path for Financial Analyst

Sorting and Searching - Concepts, Algorithms and Python Code

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Fundamentals of sorting and searching in python

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