Python Searching & Sorting Algorithms - A Practical Approach

Estefania Cassingena Navone

4.7

Based on 69 ratings

, see reviews

Estefania Cassingena Navone

Learn how to implement Searching and Sorting algorithms in Python. Understand how they work behind the scenes through a detailed visual and practical approach. Be able to relate each line of code to the actual inner workings of the algorithms as they run.

Enter the World of Computer Science and Algorithms with the Right Skills.

Learn how to implement these algorithms in Python.
Be able to explain how they work behind the scenes.
Learn how to compare them based on their efficiency.
Be able to apply them to new scenarios.

Enter the World of Computer Science and Algorithms with the Right Skills.

Learn how to implement these algorithms in Python.
Be able to explain how they work behind the scenes.
Learn how to compare them based on their efficiency.
Be able to apply them to new scenarios.

Add New Skills To Your Algorithmic Toolbox

Basic knowledge of algorithms is vital for every developer. Searching and Sorting algorithms is a key topic commonly asked during technical interviews. Be one step ahead of your competition by learning these skills with this on-demand course. Python is the most popular and approachable programming language and its popularity continues to rise year-over-year.

Having a firm grasp of Searching and Sorting algorithms will not only help you during your job search, it will also enhance your computational thinking skills. Be able to dive into more advanced algorithms with the solid foundation that this course provides. With detailed and didactic slides, animations, explanations, and exercises, you will dive into the world of algorithms through an engaging and practical learning experience.

Content & Overview

With high quality video lectures that include graphics and animations, you will learn the following algorithms:

Linear Search
Binary Search
Bubble Sort
Selection Sort
Insertion Sort
Merge Sort
Quicksort

You will also learn how to use the timeit module to time the execution of small code snippets.

Course by the Numbers

1,050+ PDF slides.
96+ quiz questions.
23+ Downloadable Python files.
10+ PDF handouts.
10 coding exercises.
9 mini projects.

Learning Material & Practice:

High-Quality Video Lectures - Carefully designed graphics and animations.
Coding Exercises with detailed solutions - Execute and test your code directly in the browser.
Mini Projects with detailed solutions - Dive deeper into each algorithm by completing a mini project per section.
Quizzes - Test your knowledge and receive instant feedback.
Code with Print Statements - See how the algorithms work behind the scenes as the code runs.
PDF Handouts - Each section has a PDF handout with a graphical and detailed summary of the algorithm.
PDF Slides - You can download the PDF slides displayed in the videos.
Articles - Detailed descriptions of key aspects of the topics to complement your knowledge.

Why is this course unique?

This course is unique because of its emphasis on providing visual and detailed explanations of how the algorithms work behind the scenes, so you will not only learn how to implement them in Python, you will also learn how they work in such detail that you will be able to explain and visualize the steps of the process, given a particular input.

You will see how the algorithms work behind the scenes as the code runs with downloadable Python files that contain implementations with carefully designed print statements. No more trying to guess what is happening behind the scenes when the algorithm runs.

You will have access to unique downloadable PDF handouts specially designed for the course (one per section) with complete and graphical descriptions of the algorithms.

If you need to learn or refresh the basics of lists, tuples, and algorithmic time complexity, the course has you covered. The Quick Refresher section offers a short but comprehensive introduction to these topics through interactive video lectures, exercises, and didactic PDF handouts.

You will check your knowledge with short Quizzes after each main lecture. The Quizzes provide instant feedback, so you can see the correct answer immediately. The quiz questions were designed to make you think more deeply about the topics presented.

You will be able to download the PDF slides used in the videos, so you can take your learning material with you even if you don't have an internet connection when you commute to work. Study algorithms anywhere, at any time.

Finally, you will practice communications skills in the Mini Projects (one per section), where you will explain how the algorithms work step by step when they are applied to a particular input. Each mini project comes with a sample answer, so you will always be able to check your solution. Being able to explain how the algorithms work is a key skill during interviews.

You are very welcome to watch the preview lectures and check out the full course curriculum.

What are you waiting for? If you are looking for an engaging, visual, and practical course, you've found it.

Add "Searching and Sorting Algorithms in Python" to your resume and showcase your new skills.

Enroll now

Or start a personal plan

And upskill with Udemy

Here's a deal for you

Save money when you learn with a deal that may be relevant to this course.

All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.

Only 16 hours left!

24-Hour Flash Sale

Close your skills gaps with online courses and save big for a limited time.

What's inside

Learning objectives

How to implement searching and sorting algorithms in python.
Visualize how they work behind the scenes as the code runs.
Compare the efficiency of these algorithms using big o notation.

Relate each line of code with its main purpose in the algorithm.
Learn the best case, the average case, and the worst case of each algorithm.
Explain how these algorithms work and apply them to new scenarios.

How to implement searching and sorting algorithms in python.
Visualize how they work behind the scenes as the code runs.
Compare the efficiency of these algorithms using big o notation.
Relate each line of code with its main purpose in the algorithm.
Learn the best case, the average case, and the worst case of each algorithm.
Explain how these algorithms work and apply them to new scenarios.

Syllabus

Welcome to the Course

You will find:

A brief introduction to the topic of the course and the evolution of searching and sorting algorithms.

You will find:

An interactive activity - Introduce yourself on the discussion forums.

Celebrate your milestone with a collectible badge.

You will find:

A brief description of the purpose of the quick refresher section.

Brief introduction to this section.

In this article you will find the study material for this section:

PDF Handout with a summary of the main aspects of Lists, Tuples, and Algorithmic Complexity.
PDF Handout with Practice Exercises.
PDF Handout with an explanation of slicing in Python.
A .zip file with the slides for this section.

You will learn:

The concept of "Algorithm" and key concepts related to algorithms.

You will learn:

The main characteristics of Lists.
How to use indices to access the elements of a List.
That Lists are Mutable and its implications.
How to traverse lists using for loops in Python.
How to use Lists built-in methods and Python functions to work with Lists.

These items are first explained and then they are demonstrated during a coding session during the lecture.

You will find:

Links to helpful resources and readings to complement your knowledge.

You will learn:

The main characteristics of Tuples.
How to use indices to access the elements of a Tuple.
That Tuples are Immutable and its implications.
How to traverse tuples using for loops in Python.
How to use Tuples' built-in methods and Python functions to work with them.

These items are first explained and then they are demonstrated during a coding session during the lecture.

You will find:

A detailed description of the key aspects of slicing in Python.
A PDF handout with this description.

You will find:

A link to download the PDF Handout with more challenging practice exercises on lists and tuples.

You will learn:

The concept of Algorithmic Time Complexity.
The different Orders of Growth.
The concepts of best case, average case, and worst case.
How to compare algorithms using Big O notation.
Why this concept is needed to learn Searching and Sorting Algorithms.

You will learn:

The meaning of c in the expression presented for Big O Notation.

You will find:

Links to helpful resources to complement your knowledge.

You will find:

Links to helpful resources to refresh your knowledge on recursion.

You will find:

A description of a possible bug that could occur when lists are extremely large and how to fix it.

You will find:

A brief introduction to the topics presented in this section.

You will find:

A PDF Handout with a graphical summary of the Linear Search algorithm.
A .zip file with the slides used during this section.

You will learn:

How the Linear Search Algorithm works step by step.
How the algorithm can be applied to a simple example.

You will learn:

How to implement the Linear Search Algorithm in Python.
What each line of code represents in the algorithm.

You will find:

The Python implementation of this algorithm.

You will learn:

The time complexity of the Liner Search Algorithm for the best case, average case, and worst case.

You will find:

A step-by-step example of the algorithm using strings.

You will find:

A brief explanation of the topics and activities in this section.

You will find:

A PDF Handout with a graphical summary of the Binary Search algorithm.
A .zip file with the slides for this section.

You will learn:

How the Binary Search algorithm works behind the scenes with step-by-step explanations.
This lecture incorporates carefully designed graphics and animations to illustrate the process.

You will learn:

How to implement the Binary Search algorithm in Python.
How to relate each line of code in the implementation to the actual process. This explanation uses carefully designed graphics and animations to illustrate the process.

You will find:

The iterative implementation of the Binary Search algorithm in Python.

You will learn:

How the recursive implementation of the Binary Search algorithm works behind the scenes.
This lecture includes carefully designed graphics and animations to illustrate the process.

You will find:

The Python code of a recursive implementation of the Binary Search Algorithm.

You will find:

An example of the Binary Search algorithm running with larger inputs.

You will learn:

The best-case, average-case, and worst-case time complexity of the Binary Search algorithm.

You will find:

A step-by-step explanation of the Binary Search algorithm applied to a list of integers.
Carefully designed graphics and animations to illustrate the process.

You will find:

A step-by-step explanation of the Binary Search algorithm applied to a list of strings.
Carefully designed graphics and animations to illustrate the process.

You will find:

A brief description of the topics and activities for this section.

You will find:

A PDF Handout with a graphical summary of the Bubble Sort algorithm.
A .zip file with the slides for this section.

You will find:

A brief description of important sorting terminology.

You will find:

A carefully designed visual walkthrough of the Bubble Sort algorithm.

You will find:

A step-by-step walkthrough of the Python implementation of the basic and optimized versions of the Bubble Sort algorithm.

You will find:

The Python code of an implementation of the Bubble Sort Algorithm.

You will find:

The Python code of an optimized implementation of the Bubble Sort Algorithm.

You will find:

A description of the best-case, average-case, and worst-case time complexities of the Bubble Sort algorithm.

You will find:

A step-by-step example of the Bubble Sort algorithm applied to a list of numbers.
Carefully designed graphics and animations to explain the process.

You will find:

A step-by-step example of the Bubble Sort algorithm applied to a list of strings.
Carefully designed graphics and animations to explain the process.

You will find:

A PDF Handout with a graphical summary of the Selection Sort algorithm.
A .zip file with the slides for this section.

You will find:

A carefully designed visual walkthrough of the Selection Sort algorithm.

You will find:

A step-by-step walkthrough of the Python implementation of the Selection Sort algorithm.

You will find:

The Python code with an implementation of the Selection Sort Algorithm.

You will find:

A description of the best-case, average-case, and worst-case time complexities of the Selection Sort algorithm.

You will find:

A step-by-step example of the Selection Sort algorithm applied to a list of numbers.
Carefully designed graphics and animations to explain the process.

You will find:

A brief explanation of the terminology used to work with strings during the course.

You will find:

A step-by-step example of the Selection Sort algorithm applied to a list of strings.
Carefully designed graphics and animations to explain the process.

You will find:

A PDF Handout with a graphical summary of the Insertion Sort algorithm.
A .zip file with the slides for this section.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Develops a strong foundation for beginners seeking to start or build upon their knowledge in searching and sorting algorithms

Emphasizes the ‘why’ behind the ‘how’ to enhance learners' understanding and critical thinking

Taught by Estefania Cassingena Navone, who is an experienced instructor in computer science and algorithms

Leverages detailed slides, animations, and explanations to enhance visual and practical learning

May be less relevant for advanced learners seeking comprehensive or specialized knowledge in searching and sorting algorithms

Save this course

Create your own learning path. Save this course to your list so you can find it easily later.

Save

Reviews summary

Practical python algorithms with visual clarity

According to its design, students would find 'Python Searching & Sorting Algorithms - A Practical Approach' to be a highly visual and practical journey into fundamental algorithms. Learners are guided through clear, step-by-step explanations complemented by engaging graphics and animations, making complex concepts easy to grasp. The course emphasizes hands-on implementation in Python, with extensive coding exercises and mini-projects that solidify understanding. It's particularly useful for technical interview preparation, offering a solid foundation and unique visual debugging tools. The included quick refreshers on core Python concepts and Big O notation ensure accessibility for various skill levels.

Includes helpful quick refreshers for essential Python concepts and Big O notation.

"The Quick Refresher section on lists, tuples, and time complexity was a great way to brush up before diving into algorithms."

"Even if I needed to refresh basics, the course had me covered with its comprehensive introduction to foundational topics."

"I could easily dive into more advanced algorithms with the solid foundation this course provided."

Provides abundant learning materials, including slides, quizzes, and code.

"The sheer volume of PDF slides, quiz questions, and downloadable Python files is impressive and helpful."

"I found the PDF handouts with graphical summaries particularly useful for quick review."

"Having quizzes after each lecture with instant feedback helped me test my knowledge effectively."

Excellent for preparing for technical interviews and enhancing algorithmic skills.

"This course helped me get one step ahead for technical interviews by explaining key topics thoroughly."

"Learning these algorithms here enhanced my computational thinking, which is vital for job search."

"Being able to explain how the algorithms work, as taught in the mini projects, is a key interview skill."

Strong focus on hands-on Python coding and real-world application.

"I can apply these algorithms to new scenarios, which is a great practical skill."

"I appreciate the focus on implementing these algorithms directly in Python."

"The coding exercises and mini-projects are essential for solidifying the concepts with hands-on practice."

Offers highly visual and animated explanations for deep understanding.

"I found the detailed visual and practical approach really helped me understand how the algorithms work behind the scenes."

"The carefully designed graphics and animations made the process incredibly clear and easy to visualize."

"It's great to finally see how the algorithms work as the code runs, without guessing what's happening."

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 Python Searching & Sorting Algorithms - A Practical Approach with these activities:

Review the basics of Python

Show steps

Ensure a strong foundation in Python, the programming language used in the course.

Browse courses on Python

Show steps

Review the basics of Python syntax.
Practice writing simple Python programs.

Find a mentor who can help you with sorting algorithms

Show steps

Connect with someone who has experience with sorting algorithms and can provide guidance and support.

Browse courses on Sorting Algorithms

Show steps

Identify your learning goals.
Find a mentor who has experience with sorting algorithms.
Reach out to your mentor and introduce yourself.
Set up regular meetings with your mentor.

Compile a list of resources on sorting algorithms

Show steps

Gather and organize resources on sorting algorithms for future reference.

Browse courses on Sorting Algorithms

Show steps

Find resources on sorting algorithms, such as articles, blog posts, and videos.
Organize the resources into a list or document.
Share your list of resources with others.

Five other activities

Expand to see all activities and additional details

Show all eight activities

Write more code

Show steps

Practice implementing the algorithms by coding them up yourself.

Browse courses on Sorting Algorithms

Show steps

Choose an algorithm to practice.
Implement the algorithm in Python.
Test your code with different inputs and compare the outputs to the expected results.
Repeat steps 1-3 for a variety of different algorithms.

Solve coding challenges

Show steps

Apply your knowledge of sorting algorithms to solve coding challenges.

Browse courses on Sorting Algorithms

Show steps

Find a coding challenge website or platform.
Choose a challenge that involves sorting algorithms.
Solve the challenge using the sorting algorithm you learned in the course.
Repeat steps 2-3 for a variety of different challenges.

Build a sorting algorithm visualizer

Show steps

Create a visual representation of a sorting algorithm to see how it works step by step.

Browse courses on Sorting Algorithms

Show steps

Choose a sorting algorithm to visualize.
Design the visual representation.
Implement the visual representation in Python.
Test your visualizer with different inputs and compare the outputs to the expected results.

Watch tutorials on advanced sorting algorithms

Show steps

Expand your knowledge of sorting algorithms by watching tutorials on advanced techniques.

Browse courses on Sorting Algorithms

Show steps

Find tutorials on advanced sorting algorithms.
Watch the tutorials and take notes.
Try to implement the algorithms you learned in your own code.

Write a blog post about your favorite sorting algorithm

Show steps

Share your knowledge and understanding of sorting algorithms by writing a blog post about them.

Browse courses on Sorting Algorithms

Show steps

Choose a sorting algorithm to write about.
Write a blog post that explains the algorithm, its advantages and disadvantages, and how it compares to other sorting algorithms.
Publish your blog post online.

Career center

Learners who complete Python Searching & Sorting Algorithms - A Practical Approach will develop knowledge and skills that may be useful to these careers:

Reading list

We haven't picked any books for this reading list yet.

Help others find this course page by sharing it with your friends and followers:

Facebook

Copy Link

Similar courses

Here are nine courses similar to Python Searching & Sorting Algorithms - A Practical Approach.

GenAI for DevOps Practitioners

Most relevant

Accelerate Migration from Control-M to Apache Airflow with DAGify

Accelerate Migration from Control-M to Apache Airflow...

Most relevant

Meta Marketing Science Certification Exam

Most relevant

Optical Character Recognition (OCR) with Document AI (Python)

Optical Character Recognition (OCR) with Document AI...

Most relevant

Data Balancing with Gen AI: Credit Card Fraud Detection

Most relevant

Programmatic Prompting with OpenAI: Refining and Filtering

Most relevant

Prerequisites and Advanced Machine Learning for NLP

Most relevant

NLP – Machine Learning Models in Python

Most relevant

PyMongo - Advanced

Most relevant

Udemy Buyer Protection & Guarantee

Verified partner policies & purchase protections

Global Marketplace Leader

Free Trial & Audit

Free Lecture Previews

Free preview video lectures available for all courses; optional 7-day free trial on Personal Plan subscriptions (cancel before trial ends to avoid conversion).

Return & Refund Policy

30-Day Money-Back Guarantee

30-day money-back guarantee on all eligible individual course purchases (provided course content has not been substantially consumed or downloaded). Subscription fees are non-refundable once billed.

Buyer Protections

Verified Academic & Industry Partner

Lifetime access to purchased individual courses and future updates, verifiable certificate of completion, and direct student Q&A forums.

Key Purchase Protections

30-day 100% money-back guarantee on course purchases

Lifetime access on web, mobile, and offline

Certificate of completion included with purchase

Direct instructor Q&A and active student community

OpenCourser Verified Partner Policy details last reviewed: 2026-10-22