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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.

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Overview

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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, including greedy algorithms and dynamic programming. At each step, you’ll review implementation details with consideration for time complexity, hands-on coding exercises, and thorough explanations of the principles at hand. By the end of this course, you’ll have the confidence to solve any problem using the fundamentals of computer programming in Go.

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

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

TAKEAWAY SKILLS

Programming Language

Data Structures

Algorithms

Content

210 Lessons2 Quizzes81 Challenges

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.

Recursive Functions

14 Lessons

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

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.

Data Structures in Go

11 Lessons

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

Sorting

17 Lessons

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

Stack

36 Lessons

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

Queue

11 Lessons

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

10.

Tree

59 Lessons

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

11.

Binary Search Tree

25 Lessons

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

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Course Author:

Hemant Jain

Developed by MAANG Engineers

Every Educative lesson is designed by a team of ex-MAANG software engineers and PhD computer science educators, and developed in consultation with developers and data scientists working at Meta, Google, and more. Our mission is to get you hands-on with the necessary skills to stay ahead in a constantly changing industry. No video, no fluff. Just interactive, project-based learning with personalized feedback that adapts to your goals and experience.

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Hands-on Learning Powered by AI

See how Educative uses AI to make your learning more immersive than ever before.

Personalized Interview Prep

Skip the LeetCode grind with a custom roadmap that adapts to your goals. Hands-on practice for Coding Interviews, System Design, and more.

Mock Interviews

Test your skills in a simulated interview setting. Receive personalized feedback based on your performance. Available for Coding Interviews, System Design, and more.

AI Prompt

Build prompt engineering skills. Practice implementing AI-informed solutions.

Code Feedback

Evaluate and debug your code with the click of a button. Get real-time feedback on test cases, including time and space complexity of your solutions.

Explain with AI

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AI Code Mentor

AI Code Mentor helps you quickly identify errors in your code, learn from your mistakes, and nudge you in the right direction — just like a 1:1 tutor!

Free Resources

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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.

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