What background knowledge is necessary to enroll in this course?

Before enrolling, you should have a basic understanding of programming, particularly in JavaScript, and familiarity with fundamental data structures such as arrays and linked lists. The course will build on these basics, so while previous experience with data structures and algorithms is helpful, it is not mandatory.

Who is this course for?

This course is aimed at intermediate programmers who wish to enhance their understanding of advanced data structures and algorithms. It is particularly useful for individuals preparing for technical interviews, competitive programming, or those looking to improve their coding efficiency in real-world applications.

How long does it take to complete the course?

The course takes approximately 13 hours to complete, making it a manageable option for learners looking to improve their skills in a relatively short period.

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.

Advanced Data Structures and Problem-Solving Techniques

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Advanced Data Structures and Problem-Solving Techniques

This course is part of Data Structures & Algorithms in JavaScript Specialization

Instructor: Packt - Course Instructors

Included with

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7 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

7 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

Implement advanced data structures such as binary search trees, heaps, and sliding window methods.
Solve complex algorithmic problems using efficient techniques like two-pointer and binary search.
Optimize problem-solving strategies for performance in coding challenges.
Master problem-solving methods essential for technical interviews and real-world applications.

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This course is part of the Data Structures & Algorithms in JavaScript Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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Develop job-relevant skills with hands-on projects
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There are 7 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. Through this course, you’ll gain a deeper understanding of advanced data structures and problem-solving techniques. You'll explore core data structures such as queues, heaps, binary search trees, and binary trees, learning how to implement and optimize them. By working through a variety of real-world coding problems, you’ll also hone your algorithmic thinking skills and ability to tackle complex coding challenges. The course is designed to walk you through the fundamentals and more advanced concepts, starting with the implementation of basic structures like queues and progressing to more intricate topics like binary search trees, heaps, and sliding window methods. You'll work with different data structures in various programming languages, including JavaScript, to optimize solutions and improve performance. As you proceed, you will also tackle problem-solving strategies using methods like sliding window, two-pointer, binary search, and dynamic programming, with ample practice problems to reinforce each technique. This course is perfect for intermediate learners familiar with basic programming concepts and data structures. If you’re looking to improve your algorithmic skills, or if you’re preparing for coding interviews, this course is the perfect way to take your understanding to the next level. By the end of the course, you will be able to implement advanced data structures, solve real-world algorithmic problems, optimize code for efficiency, and prepare for technical interviews.

In this module, we will explore the fundamentals of queues as a data structure. You will learn to implement queues using both linked lists and arrays, ensuring efficient operations. By the end of this section, you will be comfortable with practical queue implementations in JavaScript.

What's included

3 videos2 readings1 assignment

In this module, we will dive into the sliding window method, a powerful technique for optimizing algorithms. You'll apply this technique to efficiently solve problems like the "Longest Substring Without Repeating Characters" and "Sliding Window Maximum."

What's included

4 videos1 assignment

In this module, we will focus on the two-pointer technique. You'll learn to apply it in solving problems like "Trapping Rain Water" and "Container with Most Water." This method will also help you check for palindromes efficiently.

What's included

4 videos1 assignment

In this module, we will introduce you to binary search, a highly efficient algorithm for searching sorted arrays. You’ll gain hands-on experience in implementing it and solving real-world problems such as "Search Insert Position" and "Magnetic Force Between Two Balls."

What's included

6 videos1 assignment

In this module, we will introduce you to binary trees, focusing on core concepts like tree traversal and key operations. You’ll tackle problems such as "Maximum Depth of a Binary Tree" and "Invert Binary Tree" while gaining a deeper understanding of tree structures.

What's included

21 videos1 assignment

21 videosTotal 155 minutes

Introduction to Binary Trees9 minutes
Terms Related to Trees8 minutes
Level Order Traversal3 minutes
Tree Traversal Algorithms9 minutes
Practice Problem 1 - Binary Tree InOrder Traversal3 minutes
Practice Problem 2 - Maximum Depth of a Binary Tree8 minutes
Practice Problem 3 - Invert Binary Tree5 minutes
Practice Problem 4 - Binary Tree Level Order Traversal7 minutes
Practice Problem 5 - Diameter of a Binary Tree13 minutes
Practice Problem 6 - Path Sum8 minutes
Practice Problem 7 - Path Sum II10 minutes
Practice Problem 8 - Cousins in Binary Tree9 minutes
Practice Problem 9 - Maximum Level Sum of Binary Tree8 minutes
Practice Problem 10 - Symmetric Tree7 minutes
Practice Problem 11 - Balanced Binary Tree8 minutes
Practice Problem 12 - Binary Tree Right Side View3 minutes
Practice Problem 13 - Construct Binary Tree from PreOrder and InOrder Traversal11 minutes
Practice Problem 14 - Same Tree7 minutes
Practice Problem 15 - Subtree of Another Tree7 minutes
Practice Problem 16 - Sum of Left Leaves7 minutes
Practice Problem 17 - Count Good Nodes in Binary Tree7 minutes

1 assignmentTotal 15 minutes

Binary Trees - Assessment15 minutes

In this module, we will explore heaps, a tree-based structure used for priority queues. You will learn heap operations such as insertion and deletion, and solve problems like finding the "Kth Largest Element in an Array."

What's included

10 videos1 assignment

10 videosTotal 96 minutes

Introduction to Heaps11 minutes
Implementation of Heaps10 minutes
Heap Insertion6 minutes
Heap Insert Implementation12 minutes
Heap Deletion7 minutes
Heap with Custom Comparator7 minutes
Heap Deletion Implementation11 minutes
Heapify8 minutes
Practice Problem 1 - Kth Largest Element in an Array9 minutes
Practice Problem 2 - Find Median from Data Stream14 minutes

1 assignmentTotal 15 minutes

Heaps - Assessment15 minutes

In this module, we will explore Binary Search Trees (BSTs), a tree-based data structure that ensures efficient searching, insertion, and deletion. You will also solve various problems, such as "Validate Binary Search Tree" and "Lowest Common Ancestor of a BST."

What's included

8 videos1 reading3 assignments

8 videosTotal 65 minutes

Binary Search Tree and Its Applications17 minutes
Height Balanced BST1 minute
BST Insertion6 minutes
Inorder Successor & Predecessor5 minutes
BST Deletion13 minutes
Practice Problem 1 - Kth Smallest Element in BST6 minutes
Practice Problem 2 - Lowest Common Ancestor of a Binary Search Tree9 minutes
Practice Problem 3 - Validate Binary Search Tree8 minutes

1 readingTotal 10 minutes

Conclusion to the Course 'Advanced Data Structures and Problem-Solving Techniques'10 minutes

3 assignmentsTotal 90 minutes

Full Course Practice Assessment15 minutes
Binary Search Tree - Assessment15 minutes
Full Course Assessment60 minutes

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Frequently asked questions

Advanced Data Structures and Problem-Solving Techniques is a course designed to deepen your understanding of various data structures and algorithms, which are critical to solving complex computational problems efficiently. This specialization covers a range of advanced techniques such as sliding window methods, binary search, heaps, binary trees, and their applications in problem-solving. It is relevant because mastering these techniques can significantly improve your ability to tackle challenges in coding interviews, software development, and competitive programming.

This course covers a range of essential data structures and algorithms, including queues, binary trees, heaps, and binary search, along with problem-solving strategies. You will learn how to implement and apply these techniques in solving practical algorithmic problems. The course also includes a variety of exercises to help reinforce the concepts, making it both a theoretical and practical learning experience.

Upon completing the course, you will be able to confidently implement advanced data structures and apply algorithms to solve a wide variety of coding problems. You will be able to use techniques like binary search, sliding window, two-pointer methods, and binary tree traversals to optimize problem-solving and improve the efficiency of your code.