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Data Structures & Algorithms In Go

Gain insights into data structures and algorithms in Go. Delve into arrays, stacks, queues, hash tables, trees, greedy algorithms, and dynamic programming with hands-on coding.

Beginner

210 Lessons

55h

Certificate of Completion

Gain insights into data structures and algorithms in Go. Delve into arrays, stacks, queues, hash tables, trees, greedy algorithms, and dynamic programming with hands-on coding.

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This course includes

128 Playgrounds

81 Challenges

Course Overview

What You'll Learn

Course Content

Course Overview

Data structures and algorithms are central concepts of computer science in general and software development in particular. Logging, transforming, and analyzing data are core skills in both real-world applications and coding interviews. This course is a detailed guide for data structures and algorithms with specific applications in the Go programming language. You’ll learn basic data structures starting with arrays, stacks, queues, hash tables, and trees. You’ll then process the data with common techniques,...Show More

Data structures and algorithms are central concepts of computer science in general and software development in particular. Loggi...Show More

TAKEAWAY SKILLS

Programming Language

Data Structures

Algorithms

What You'll Learn

A strong understanding of fundamental data structures and algorithms in Go

The ability to implement common data structures in Go

The ability to process data using basic algorithms in Go

Familiarity with computer science fundamentals and Go

A strong understanding of fundamental data structures and algorithms in Go

Course Content

Getting Started

1 Lessons

Get familiar with pursuing a Go programming career with in-depth data structures.

Who Should Take this Course and Why?

Time Complexity

9 Lessons

Discover the logic behind time complexity, asymptotic notations, and algorithm efficiency.

Introduction and Asymptotic Analysis

Big-O, Omega and Theta Notations

Complexity Analysis of Algorithms

Time Complexity Order

Deriving an Algorithm's Runtime Function

Examples Related to Time Complexities

Master Theorem

Master Theorem Examples

Quiz

Arrays

23 Lessons

Go hands-on with array manipulation, searching algorithms, and various efficiency challenges.

Challenge: Sum Array

Solution Review: Sum Array

Challenge: Sequential Search

Solution Review: Sequential Search

Challenge: Binary Search

Solution Review: Binary Search

Challenge: Finding the Largest Sum Subarray

Solution Review: Finding the Largest Sum Subarray

Challenge: Rotating an Array by k Positions

Solution Review: Rotating an Array by k Positions

Challenge: Array Waveform

Solution Review: Array Waveform

Challenge: Index Array

Solution Review: Index Array

Challenge: Sorting From 1 to n

Solution Review: Sorting From 1 to n

Challenge: Smallest Positive Missing Number

Solution Review: Smallest Positive Missing Number

Challenge: Maximum, Minimum Array

Solution Review: Maximum, Minimum Array

Challenge: Array Index Maximum Difference

Solution Review: Array Index Maximum Difference

Quiz: Arrays

Recursive Functions

14 Lessons

Grasp the fundamentals of recursive functions, including factorials, GCD, Fibonacci, permutations, and the Tower of Hanoi.

Recursive Functions

Challenge: Factorial

Solution Review: Factorial

Challenge: Print Base 16 Integers

Solution Review: Print Base 16 Integers

Challenge: Greatest Common Divisor

Solution Review: Greatest Common Divisor

Challenge: Fibonacci Numbers

Solution Review: Fibonacci Numbers

Challenge: All Permutations of an Integer List

Solution Review: All Permutations of an Integer List

Challenge: Tower of Hanoi

Solution Review: Tower of Hanoi

Quiz: Recursion

Approaches to Solve Algorithm Design Problems

4 Lessons

Take a closer look at identifying constraints, generating ideas, assessing complexities, and thorough testing in algorithm design.

Introduction and Constraints

Idea Generation

Complexities, Coding, and Testing

Example and Summary

Data Structures in Go

11 Lessons

Simplify complex data structures in Go, from ADTs to advanced collections like graphs.

Abstract Data Type

Go Collection Framework

Stack

Queue

Tree

Priority Queue / Heap

Sorting

17 Lessons

Build on sorting principles, techniques, and algorithms for various dataset scenarios.

External Sort (External Merge-Sort)

Stable Sort

Choosing the Best Sorting Algorithm

Challenge: Partitioning of 0s and 1s

Solution Review: Partitioning of 0s and 1s

Challenge: Partitioning of 0s, 1s, and 2s

Solution Review: Partitioning of 0s, 1s and 2s

Stack

36 Lessons

Sharpen your skills in implementing and managing stacks, including operations, challenges, and expression conversions.

Introduction to Stack

The Stack Abstract Data Type

Challenge: Stack Using Array

Solution Review: Stack Using Array

Challenge: Stack Using Linked List

Solution Review: Stack Using Linked List

System Stack and Method Calls

Challenge: Sorted Insert

Solution Review: Sorted Insert

Challenge: Sort Stack

Solution Review: Sort Stack

Challenge: Bottom Insert

Solution Review: Bottom Insert

Challenge: Reverse Stack

Solution Review: Reverse Stack

Challenge: Reverse k Elements in a Stack

Solution Review: Reverse k Element in a Stack

Challenge: Balanced Parentheses

Solution Review: Balanced Parenthesis

Challenge: Min Stack

Solution Review: Min Stack

Challenge: Max Depth Parenthesis

Solution Review: Max Depth Parenthesis

Challenge: Longest Continuous Balanced Parenthesis

Solution Review: Longest Continuous Balanced Parenthesis

Challenge: Reverse Parenthesis

Solution Review: Reverse Parentheses

Challenge: Find Duplicate Parentheses

Solution Review: Find Duplicate Parenthesis

Challenge: Print Parenthesis Number

Solution Review: Print Parentheses Number

Infix, Prefix, and Postfix Expressions

Challenge: Infix-to-Postfix Conversion

Solution Review: Infix-to-Postfix Conversion

Challenge: Infix-to-Prefix Conversion

Solution Review: Infix-to-Prefix Conversion

Queue

11 Lessons

Unpack the core of queue data structures, their implementations, and problem-solving techniques.

Introduction to Queue

Queue Implementation Using an Array

Queue Implementation Using a LinkedList

Queue Implementation Using Circular Linked List

Queue Implementation Using Doubly Linked List

Challenge: Queue Using Stack

Solution Review: Queue Using Stack

Challenge: Reverse Queue

Solution Review: Reverse Queue

Challenge: Reverse k Elements in a Queue

Solution Review: Reverse k Elements in a Queue

10.

Tree

59 Lessons

Examine tree structures, types, and traversals, with practical challenges and efficient solutions.

Introduction to Tree

Types of Trees

Introduction to Binary Trees

Challenge: Create a Complete Binary Tree

Solution Review: Create a Complete Binary Tree

Challenge: Print Pre-Order Traversal

Solution Review: Print Pre-Order Traversal

Challenge: Print Post-order Traversal

Solution Review: Print Post-order Traversal

Challenge: Print In-order Traversal

Solution Review: Print In-Order Traversal

Challenge: Print level-order Traversal

Solution Review: Print Level-order Traversal

Challenge: Print Depth First Without Recursion

Solution Review: Print Depth First Without Using the Recursion

Challenge: Print Level Order Line by Line Using Two Queues

Solution Review: Print Level Order Line by Line Using Two Queues

Challenge: Print a Tree in Level-order Line by Line Using a Queue

Solution Review: Print Level Order Line by Line Using One Queue

Challenge: Print Spiral Tree

Solution Review: Print Spiral Tree

Challenge: nth Pre-order

Solution Review: nth Pre-Order

Challenge: nth Post-order

Solution Review: nth Post-Order

Challenge: nth In-Order

Solution Review: nth In-Order

Challenge: Print All the Paths

Solution Review: Print All the Paths

Challenge: Number of Elements

Solution Review: Number of Elements

Challenge: Sum of All Nodes in a Binary Tree

Solution Review: Sum of All Nodes in a Binary Tree

Challenge: Find Number of Leaf Nodes

Solution Review: Find Number of Leaf Nodes

Challenge: Number of Full Nodes in a Binary Tree

Solution Review: Number of Full Nodes in a Binary Tree

Challenge: Search Value in a Binary Tree

Solution Review: Search Value in a Binary Tree

Challenge: Find Max in Binary Tree

Solution Review: Find Max in Binary Tree

Challenge: Tree Depth

Solution Review: Tree Depth

Challenge: Identical Trees

Solution Review: Identical Trees

Challenge: Copy Tree

Solution Review: Copy Tree

Challenge: Copy Mirror Tree

Solution Review: Copy Mirror Tree

Challenge: Free Tree

Solution Review: Free Tree

Challenge: Check Completeness of Tree Using Queue

Solution Review: Check Completeness of Tree Using Queue

Challenge: Check Completeness of Tree Using Recursion

Solution Review: Check Completeness of Tree using Recursion

Challenge: Is Tree a Heap?

Solution Review: Is Tree a Heap

Challenge: Tree to List Conversion using Recursion

Solution Review: Tree to List Conversion using Recursion

11.

Binary Search Tree

25 Lessons

Grasp the fundamentals of Binary Search Trees, covering construction, insertion, deletion, and tree traversal.

Introduction to a Binary Search Tree (BST)

Challenge: Create a Binary Search Tree From the Sorted List

Solution Review: Create a Binary Search Tree From the Sorted List

Challenge: Insertion

Solution Review: Insertion

Challenge: Find Node

Solution Review: Find Node

Challenge: Find Min

Solution Review: Find Min

Challenge: Find Max

Solution Review: Find Max

Challenge: Is It a BST?

Solution Review: Is It a BST?

Challenge: Delete Node

Solution Review: Delete Node

Challenge: Least Common Ancestor

Solution Review: Least Common Ancestor

Challenge: Print Tree Nodes within a Range

Solution Review: Print Tree Nodes within a Range

Challenge: Trim the Tree Nodes Outside Range

Solution Review: Trim the Tree Nodes Outside Range

Challenge: Find Ceil and Floor Values in a BST

Solution Review: Find Ceil and Floor Values in a BST

Challenge: Is It a BST Array?

Solution Review: Is It a BST Array?

Course Author

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Frequently Asked Questions

What is the goal of this course?

The course aims to teach data structures and algorithms, specifically within the Go programming language.

Who is this course for?

It’s ideal for developers who want to build a strong foundation in Go and understand how to apply data structures and algorithms.

What types of data structures will I learn?

You’ll learn about arrays, stacks, queues, hash tables, and trees.

Does the course cover algorithmic techniques?

It includes greedy algorithms, dynamic programming, and other core techniques.

What is the teaching format of the course?

The course comprises lectures, coding exercises, detailed explanations, and hands-on examples in Go.

Are advanced algorithms covered?

Yes, the course goes beyond basics and covers dynamic programming, greedy algorithms, and more.

Is there any real-world application of the Go algorithms discussed?

Yes, the course applies algorithms to practical, real-world problems, focusing on efficient data processing in Go.