Kick Butt in Coding Interviews: Data Structures in Python

  • Created by Alvin Wan
  • Course Duration 2 hours 59 mins
  • Price USD$Free
  • User Rating
  • Platform Coursera
  • Course Link Explore Course
No idea how to get ready for coding interviews? The answer lies in understanding practical benefits of an age-old computer science 101 topic: data structures. This class covers a must-know topic for every programmer: data structures. We’ll cover several concepts and takeaways:

Are you preparing for coding interviews but feeling overwhelmed? The key to success lies in understanding the practical benefits of an age-old computer science 101 topic: data structures. If you want to ace coding interviews and stand out from the competition, mastering data structures is essential. Join our online course today and gain the knowledge and skills to kick butt in coding interviews!


In today’s highly competitive tech industry, coding interviews play a crucial role in landing your dream job. Companies often evaluate candidates based on their understanding of data structures and algorithms. That’s why it’s vital to have a strong foundation in data structures. This article introduces our comprehensive online course, “Kick Butt in Coding Interviews: Master Data Structures in Python,” designed to help you succeed in coding interviews.

Importance of Data Structures in Coding Interviews

Data structures are the building blocks of efficient algorithms. They allow us to organize and store data in a way that optimizes memory usage, improves search and retrieval operations, and enhances overall program efficiency. In coding interviews, interviewers often assess candidates’ ability to select and implement appropriate data structures to solve complex problems. By mastering data structures, you can demonstrate your problem-solving skills and logical thinking, giving you a competitive edge in coding interviews.

Overview of the Online Course

Our online course is structured to provide you with a comprehensive understanding of data structures and equip you with the necessary skills to tackle coding interviews with confidence. Taught by industry leaders and working professionals, the course offers a dynamic and interactive learning experience. Through a combination of video lectures, coding exercises, and interview-style practice questions, you’ll develop a solid foundation in data structures.

Course Overview

Curriculum Highlights

Our course covers a wide range of topics essential for mastering data structures in Python. Here are some key highlights:

  • Analyzing and understanding algorithm “efficiency” using orders of growth analysis.
  • Exploring commonly-used data structures such as stacks, queues, linked lists, trees, and hash maps.
  • Deep dive into data structure algorithms, including insertion, deletion, search, and access operations.
  • Understanding the practical implications of data structures’ strengths and weaknesses.
  • Solving 28 in-depth interview-style practice questions designed to enhance your problem-solving skills.
  • 20 valuable interview tips to help you excel in coding interviews.

Interactive Learning Experience

We believe in learning by doing. Throughout the course, you’ll have numerous opportunities to code alongside the instructor. By actively engaging in coding exercises and implementing data structures in Python, you’ll reinforce your understanding and gain practical experience. Our interactive learning environment fosters hands-on learning, ensuring that you’re well-prepared for real-world coding challenges.

What You’ll Gain

By enrolling in our course, you’ll acquire essential knowledge and skills related to data structures. Here’s what you can expect to gain:

Analyzing Algorithm Efficiency

You’ll learn how to evaluate and analyze the efficiency of algorithms using orders of growth analysis. Understanding algorithmic complexity and runtime performance is crucial when optimizing code and solving complex programming problems.

Understanding Common Data Structures

We’ll delve into commonly-used data structures such as stacks, queues, linked lists, trees, and hash maps. Through detailed explanations and practical examples, you’ll gain a deep understanding of each data structure’s characteristics, operations, and best use cases.

Practical Implications of Data Structures

Data structures have real-world implications. You’ll discover how different data structures impact program efficiency, memory usage, and the ability to solve specific problems. Understanding these practical implications will enable you to make informed decisions when choosing the right data structure for a given problem.

Who This Course is For

Our course caters to a wide range of individuals who want to excel in coding interviews and enhance their data structures skills. This course is suitable for:

  • Aspiring programmers who want to strengthen their knowledge of data structures and improve their problem-solving abilities.
  • Students preparing for coding interviews at top tech companies and universities.
  • Professionals who wish to update their data structures knowledge and stay competitive in the job market.

Whether you’re a beginner or an experienced programmer, this course provides valuable insights and practical guidance for mastering data structures in Python.

Data Structures: Stacks, Queues, and Linked Lists

Exploring Stacks and Their Applications

Stacks are fundamental data structures with various applications. In this section, you’ll learn how stacks work, their key properties, and how to implement them in Python. We’ll explore real-world examples where stacks are used, such as managing function calls, implementing the undo feature, and evaluating arithmetic expressions.

Understanding Queues and Their Usage

Queues are another essential data structure that follows the First-In-First-Out (FIFO) principle. You’ll discover how to implement queues, explore their operations, and understand their relevance in scenarios like task scheduling, message processing, and breadth-first search algorithms.

Mastering Linked Lists and Their Advantages

Linked lists are versatile data structures used to store and manage collections of elements. You’ll delve into the intricacies of linked lists, understanding their various types, such as singly linked lists, doubly linked lists, and circular linked lists. We’ll discuss their advantages, disadvantages, and their applications in scenarios like dynamic memory allocation, representing polynomials, and more.

Data Structures: Trees and Hash Maps

Introduction to Tree Structures

Trees are hierarchical data structures widely used in computer science. In this section, we’ll introduce different types of trees, including binary trees, balanced trees, and binary search trees. You’ll learn how to traverse trees, perform common operations, and explore applications like file systems, decision trees, and network routing.

Practical Use Cases of Trees

Trees have a wide range of applications in various domains. We’ll delve into practical examples where trees are used, such as representing hierarchical relationships, implementing sorting and searching algorithms, and creating efficient data storage structures.

Leveraging the Power of Hash Maps

Hash maps (also known as hash tables or dictionaries) are efficient data structures that provide constant-time access to stored elements. You’ll explore how hash maps work, understand collision resolution techniques, and learn about their applications in areas like spell checking, caching, and database indexing.

Analysis of Data Structure Algorithms

To gain a comprehensive understanding of data structures, it’s essential to analyze the algorithms associated with them. In this section, we’ll delve into the analysis of data structure algorithms, covering crucial aspects such as insertion, deletion, search, and access operations. You’ll learn how to evaluate algorithm efficiency and make informed choices based on runtime complexity.

Insertion, Deletion, Search, and Access

We’ll discuss the algorithms used for inserting, deleting, searching, and accessing elements in various data structures. By understanding the inner workings of these operations, you’ll be equipped to optimize code and improve the overall performance of your programs.

Evaluating Algorithm Efficiency with Orders of Growth Analysis

Orders of growth analysis provides a framework for evaluating and comparing the efficiency of algorithms. We’ll dive into this analysis technique, exploring big O notation and analyzing the best, worst, and average-case complexities of data structure algorithms. This knowledge will help you optimize your code and choose the most efficient data structures for specific use cases.

Interview-Style Practice Questions and Tips

To excel in coding interviews, practice is key. In this section, you’ll have the opportunity to solve 28 in-depth interview-style practice questions. These questions cover various data structures and algorithms, allowing you to apply your knowledge and sharpen your problem-solving skills. Additionally, we’ll provide you with 20 valuable tips to help you perform your best in coding interviews. With practice and effective strategies, you’ll gain confidence and increase your chances of success.


Mastering data structures is crucial for excelling in coding interviews and becoming a successful programmer. Our online course, “Kick Butt in Coding Interviews: Master Data Structures in Python,” provides a comprehensive learning experience that will equip you with the knowledge and skills needed to ace your next coding interview. Enroll today and take the first step toward unlocking your full potential as a programmer.


  1. Q: Is this course suitable for beginners with no prior programming experience?
    • A: Yes, this course is designed to cater to beginners as well as experienced programmers. We provide detailed explanations and examples to ensure everyone can grasp the concepts.
  2. Q: Can I access the course materials at my own pace?
    • A: Yes, once you enroll in the course, you’ll have unlimited access to the materials, allowing you to learn at your own pace and revisit the content whenever needed.
  3. Q: Are there any prerequisites for this course?
    • A: Basic knowledge of programming concepts and Python syntax is beneficial, but not mandatory. We’ll cover the fundamentals of data structures in Python as part of the course.
  4. Q: How long will it take to complete the course?
    • A: The course duration depends on your learning pace. On average, it takes approximately X weeks to complete. However, you can take more or less time based on your availability and commitment.
  5. Q: Is there any support available if I have questions during the course?
    • A: Yes, we provide dedicated support to our students. You can reach out to our instructors and ask questions related to the course content or any challenges you encounter.