What background knowledge is necessary to enroll into the course?

Basic programming knowledge in any language such as Python, Java, or C++ is recommended to get the most out of this course. Familiarity with simple programming constructs like loops, conditionals, and functions will help you follow along more easily, but no advanced knowledge of algorithms is required.

Who is this course for?

This course is ideal for beginners who want to build a strong foundation in data structures and algorithms, students preparing for coding interviews, and developers looking to improve their problem-solving skills. It is also suitable for anyone aiming to practice and master common interview questions using platforms like LeetCode.

How long does it take to complete the course?

The course takes approximately 8 hours to complete, making it a concise yet comprehensive introduction that can be finished in a short period while still covering all essential concepts and practice problems.

Can I preview a course before enrolling?

Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

When will I have access to the lectures and assignments?

If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

What will I get when I enroll?

Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.

When will I receive my Course Certificate?

If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.

Why can’t I audit this course?

This course is currently available only to learners who have paid or received financial aid, when available.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Introduction to Data Structures and Algorithmic Foundations

Introduction to Data Structures and Algorithmic Foundations

Instructor: Packt - Course Instructors

Included with

Learn more

6 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

6 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Analyze algorithm efficiency using time and space complexity, including recursive cases, to write optimized and scalable solutions.
Apply Big O notation confidently to evaluate and compare different algorithmic approaches in coding interviews and real-world scenarios.
Solve array, linked list, and hash table problems using structured problem-solving techniques and industry-standard coding practices.
Approach coding interviews strategically using Leetcode-style problems while improving logical thinking and debugging skills.

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This course is part of the LEETCODE In C++ - Top 100 Coding Interview Problems Specialization

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There are 6 modules in this course

This course features Coursera Coach!

A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Build a strong foundation in data structures and algorithms to confidently tackle coding interviews and real-world problem solving. You will learn how to analyze time and space complexity, apply Big O notation, and understand how efficient code impacts performance. Through hands-on practice, you will strengthen your logical thinking and develop a problem-solving mindset essential for technical roles. The course begins with an introduction to coding interview preparation using Leetcode, guiding you on how to approach problems strategically. It then dives deep into time and space complexity, covering both theoretical concepts and practical examples, including recursive cases and live demonstrations to reinforce your understanding. As you progress, you will explore core data structures such as arrays, linked lists, and hash tables, learning their strengths, limitations, and real-world applications. Each section is paired with carefully selected problems, including popular interview questions like Two Sum, Maximum Subarray, and Linked List Cycle, enabling you to apply concepts effectively. This course is ideal for aspiring software engineers, students, and professionals preparing for coding interviews. Basic programming knowledge is recommended, and the course is designed at a beginner to intermediate level for gradual skill development. By the end of the course, you will be able to analyze algorithm efficiency, solve complex coding problems using key data structures, and confidently approach technical interviews with optimized solutions.

In this module, we will introduce Leetcode, offering insights and strategies to help you get started with your coding interview preparation. By the end of this section, you’ll be equipped with the knowledge to confidently begin solving problems on Leetcode.

What's included

1 video2 readings

In this module, we will cover essential concepts of time and space complexity, focusing on Big O notation and how to apply it in coding interviews. You’ll learn through a series of examples, helping you build a strong foundation in algorithm analysis.

What's included

13 videos1 assignment

13 videosTotal 84 minutes

Introduction To Time & Space Complexity6 minutes
What is Big O Notation?8 minutes
Calculating Time Complexity Example 110 minutes
Checking If Big O Notation Is Acceptable In Interviews11 minutes
Calculating Time Complexity Example 29 minutes
Myth About Time Complexity3 minutes
Calculating Time Complexity Of Recursive Cases7 minutes
Recursive Time Complexity Example 29 minutes
Time Complexity Live Demonstration3 minutes
Introduction To Space Complexity5 minutes
Space Complexity Calculation Simple Case6 minutes
Recursive Space Complexity Example 14 minutes
Recursive Space Complexity Example 23 minutes

1 assignmentTotal 15 minutes

Time & Space Complexity Analysis - Assessment15 minutes

In this module, we will explore arrays, discussing their advantages, limitations, and practical applications. We’ll dive into a series of Leetcode problems that will give you hands-on experience with arrays and improve your problem-solving skills.

What's included

10 videos1 assignment

10 videosTotal 77 minutes

What are arrays and why are they so fast?!7 minutes
Drawbacks Of Using Arrays6 minutes
How Do Resizable Arrays Work7 minutes
Practice Problem 1 - Max Consecutive Ones5 minutes
Practice Problem 2 - Best Time To Buy And Sell Stock8 minutes
Practice Problem 3 - Product Of Array Except Self7 minutes
Practice Problem 4 - Rotate Array8 minutes
Practice Problem 5 - Maximum Sum Subarray8 minutes
Practice Problem 6 - Maximum Product Subarray9 minutes
Practice Problem 7 - Valid Sudoku12 minutes

1 assignmentTotal 15 minutes

Arrays Theory + Leetcode Problems - Assessment15 minutes

In this module, we will solve various sorting-related problems that are commonly asked in coding interviews. You will gain practical experience with sorting algorithms while tackling problems like moving zeros and sorting colors.

What's included

3 videos1 assignment

In this module, we will delve into linked lists, exploring both basic and advanced problems. Through solving problems like reversing a linked list and detecting cycles, you’ll strengthen your linked list problem-solving abilities.

What's included

9 videos1 assignment

9 videosTotal 104 minutes

Practice Problem 1 - Intersection Of Two Linked Lists17 minutes
Practice Problem 2 - Merge Two Sorted Lists10 minutes
Practice Problem 3 - Linked List Cycle8 minutes
Practice Problem 4 - Reverse Linked List11 minutes
Practice Problem 5 - Palindrome Linked List22 minutes
Practice Problem 6 - Linked List Cycle II8 minutes
Practice Problem 7 - Find Middle Of The Linked List7 minutes
Practice Problem 8 - Remove Nth Node From End Of List10 minutes
Practice Problem 9 - Add Two Numbers11 minutes

1 assignmentTotal 15 minutes

Linked Lists - Assessment15 minutes

In this module, we will introduce hash tables and explore their functionality in solving complex coding challenges. You’ll practice using hash tables to address problems such as detecting duplicates and grouping anagrams effectively.

What's included

9 videos1 reading3 assignments

9 videosTotal 97 minutes

Introduction to Hash Table6 minutes
How does Hash Table work8 minutes
Hash Table Collision Resolution9 minutes
Practice Problem 1 - Contains Duplicate3 minutes
Practice Problem 2- Two Sum10 minutes
Practice Problem 3 - Valid Anagram2 minutes
Practice Problem 4 - Group Anagrams9 minutes
Practice Problem 5- Longest Consecutive Sequence24 minutes
Practice Problem 6 - Three Sum27 minutes

1 readingTotal 10 minutes

Conclusion to the Course 'Introduction to Data Structures and Algorithmic Foundations'10 minutes

3 assignmentsTotal 90 minutes

Hash Table - Assessment15 minutes
Full Course Assessment60 minutes
Full Course Practice Assessment15 minutes

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Frequently asked questions

Data Structures and Algorithmic Foundations refer to the core concepts used to organize data efficiently and solve computational problems effectively. This knowledge is highly relevant because it forms the backbone of software development and is essential for performing well in technical interviews, competitive programming, and real-world problem-solving scenarios.

This course provides a comprehensive introduction to fundamental data structures and algorithmic thinking. It covers key topics such as time and space complexity, Big O notation, arrays, sorting techniques, linked lists, and hash tables, along with practical problem-solving using platforms like LeetCode to reinforce learning through real coding challenges.

After completing this course, you will be able to analyze algorithms using time and space complexity, understand and implement core data structures like arrays, linked lists, and hash tables, and confidently solve common coding interview problems. You will also develop problem-solving skills that are essential for technical interviews and programming tasks.