Grow your proficiency in Golang by learning about algorithm design, analysis, and use of common Golang data structures by solving coding exercises.

Beginner

210 Lessons

55h

Certificate of Completion

Grow your proficiency in Golang by learning about algorithm design, analysis, and use of common Golang data structures by solving coding exercises.

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Explanations

This course includes

128 Playgrounds

81 Challenges

This course includes

128 Playgrounds

81 Challenges

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,...

TAKEAWAY SKILLS

Go

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

What You'll Learn

A strong understanding of fundamental data structures and algorithms in Go

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Course Content

1.

Getting Started

This chapter outlines the course scope, objectives, and prerequisites for the Go programmers.

2.

Time Complexity

In this chapter, you will learn about time complexity, analyzing algorithms with notations, runtime functions, and the Master Theorem.

Introduction and Asymptotic AnalysisBig-O, Omega and Theta NotationsComplexity Analysis of AlgorithmsTime Complexity OrderDeriving an Algorithm's Runtime FunctionExamples Related to Time ComplexitiesMaster TheoremMaster Theorem ExamplesQuiz

3.

Arrays

This chapter explores array challenges, covering tasks like searching, rotation, and pattern formation, with solutions for each problem.

Challenge: Sum ArraySolution Review: Sum ArrayChallenge: Sequential SearchSolution Review: Sequential SearchChallenge: Binary SearchSolution Review: Binary SearchChallenge: Finding the Largest Sum SubarraySolution Review: Finding the Largest Sum SubarrayChallenge: Rotating an Array by k PositionsSolution Review: Rotating an Array by k PositionsChallenge: Array WaveformSolution Review: Array WaveformChallenge: Index ArraySolution Review: Index ArrayChallenge: Sorting From 1 to nSolution Review: Sorting From 1 to nChallenge: Smallest Positive Missing NumberSolution Review: Smallest Positive Missing NumberChallenge: Maximum, Minimum ArraySolution Review: Maximum, Minimum ArrayChallenge: Array Index Maximum DifferenceSolution Review: Array Index Maximum DifferenceQuiz: Arrays

4.

Recursive Functions

This chapter covers recursive functions, including factorials, GCD, permutations, and their solutions with complexity analysis.

Recursive FunctionsChallenge: FactorialSolution Review: FactorialChallenge: Print Base 16 IntegersSolution Review: Print Base 16 IntegersChallenge: Greatest Common DivisorSolution Review: Greatest Common DivisorChallenge: Fibonacci NumbersSolution Review: Fibonacci NumbersChallenge: All Permutations of an Integer ListSolution Review: All Permutations of an Integer ListChallenge: Tower of HanoiSolution Review: Tower of HanoiQuiz: Recursion

5.

Approaches to Solve Algorithm Design Problems

In this chapter, you will learn to solve algorithm design problems by understanding constraints, idea generation, complexities, coding, and testing.

6.

Data Structures in Go

11 Lessons

This chapter explores data structures in Go, such as stacks, queues, trees, heaps, hash tables, and graphs, along with their applications.

7.

Sorting

17 Lessons

This chapter explains sorting algorithms, their efficiencies, and applications, helping you choose the best method for data.

8.

Stack

36 Lessons

In chapter discovers stacks and their last-in-first-out operations through challenges like sorting, parentheses management, and expression conversion.

9.

Queue

11 Lessons

This chapter covers queues, exploring implementations with various data structures and challenges involving basic operations.

10.

Tree

59 Lessons

This chapter explores tree structures, traversals, and challenges like searching, paths, and node calculations, focusing on hierarchical relationships.

11.

Binary Search Tree

25 Lessons

In this chapter, you will learn about Binary Search Trees, covering creation, insertion, searching, validation, and operations to maintain tree integrity.

Course Author

Trusted by 1.4 million developers working at companies

Anthony Walker

@_webarchitect_

Evan Dunbar

ML Engineer

Carlos Matias La Borde

Software Developer

Souvik Kundu

Front-end Developer

Vinay Krishnaiah

Software Developer

Eric Downs

Musician/Entrepeneur

Kenan Eyvazov

DevOps Engineer

Souvik Kundu

Front-end Developer

Eric Downs

Musician/Entrepeneur

Anthony Walker

@_webarchitect_

Evan Dunbar

ML Engineer

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Frequently Asked Questions

What is the goal of this course?

Who is this course for?

What types of data structures will I learn?

Does the course cover algorithmic techniques?

What is the teaching format of the course?

Are advanced algorithms covered?

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