NeetCode Roadmap for LeetCode problems
This roadmap contains a list of LeetCode problems (with detailed solutions) hierarchically divided into topics which can help anyone understand the world of algorithms and data structures.
Link: https://neetcode.io/roadmap
LeetCode Explore: https://leetcode.com/explore/
Navigational hashtags: #armknowledgesharing #armtutorials
General hashtags: #leetcode #algorithms #datastructures #interviewpreparation #technicalinterview
@data_science_weekly
This roadmap contains a list of LeetCode problems (with detailed solutions) hierarchically divided into topics which can help anyone understand the world of algorithms and data structures.
Link: https://neetcode.io/roadmap
LeetCode Explore: https://leetcode.com/explore/
Navigational hashtags: #armknowledgesharing #armtutorials
General hashtags: #leetcode #algorithms #datastructures #interviewpreparation #technicalinterview
@data_science_weekly
Основы алгоритмов
С помощью этого хендбука вы научитесь проектировать, оптимизировать, комбинировать и отлаживать алгоритмы — причём без привязки к какому-либо языку программирования. Кроме теории мы собрали и практические задания разного уровня сложности, а также подготовили систему автоматической проверки эффективности алгоритмов — всё это поможет вам закрепить и отточить новые навыки.
Link: https://academy.yandex.ru/handbook/algorithms
Navigational hashtags: #armknowledgesharing #armcourses
General hashtags: #algorithms #datastructures #datastructuresandalgorithms #python
@data_science_weekly
С помощью этого хендбука вы научитесь проектировать, оптимизировать, комбинировать и отлаживать алгоритмы — причём без привязки к какому-либо языку программирования. Кроме теории мы собрали и практические задания разного уровня сложности, а также подготовили систему автоматической проверки эффективности алгоритмов — всё это поможет вам закрепить и отточить новые навыки.
Link: https://academy.yandex.ru/handbook/algorithms
Navigational hashtags: #armknowledgesharing #armcourses
General hashtags: #algorithms #datastructures #datastructuresandalgorithms #python
@data_science_weekly
education.yandex.ru
Основы алгоритмов — Хендбук от Яндекс Образования
С точки зрения проектирования и реализации алгоритмов есть много хороших, ставших классическими, учебных пособий, в нашем хендбуке мы пробуем подходить к выявлению общих принципов через решение задач.
Algorithmic concepts by Afshine Amidi and Shervine Amidi
This guide is a concise and illustrated guide for anyone who wants to brush up on their fundamentals in the context of coding interviews, computer science classes or to satisfy their own curiosity.
It is divided into 4 parts
- Foundations: main types of algorithms and related mathematical concepts
- Data structures: arrays, strings, queues, stacks, hash tables, linked lists and associated theorems and tricks
- Graphs and trees: graph concepts and graph traversal algorithms along with important types of trees
- Sorting and search: common, efficient sorting and search algorithms
Link
https://superstudy.guide/algorithms-data-structures/foundations/algorithmic-concepts
Navigational hashtags: #armknowledgesharing #armtutorials
General hashtags: #algorithms #datastructures #datastructuresandalgorithms #graphs #trees #sorting #search
@data_science_weekly
This guide is a concise and illustrated guide for anyone who wants to brush up on their fundamentals in the context of coding interviews, computer science classes or to satisfy their own curiosity.
It is divided into 4 parts
- Foundations: main types of algorithms and related mathematical concepts
- Data structures: arrays, strings, queues, stacks, hash tables, linked lists and associated theorems and tricks
- Graphs and trees: graph concepts and graph traversal algorithms along with important types of trees
- Sorting and search: common, efficient sorting and search algorithms
Link
https://superstudy.guide/algorithms-data-structures/foundations/algorithmic-concepts
Navigational hashtags: #armknowledgesharing #armtutorials
General hashtags: #algorithms #datastructures #datastructuresandalgorithms #graphs #trees #sorting #search
@data_science_weekly
Harvard CS50 (2023) – Full Computer Science University Course
This is CS50, Harvard University’s introduction to the intellectual enterprises of computer science and the art of programming, for concentrators and non-concentrators alike, with or without prior programming experience. (Two thirds of CS50 students have never taken CS before.) This course teaches you how to solve problems, both with and without code, with an emphasis on correctness, design, and style. Topics include computational thinking, abstraction, algorithms, data structures, and computer science more generally. Problem sets inspired by the arts, humanities, social sciences, and sciences. More than teach you how to program in one language, this course teaches you how to program fundamentally and how to teach yourself new languages ultimately. The course starts with a traditional but omnipresent language called C that underlies today’s newer languages, via which you’ll learn not only about functions, variables, conditionals, loops, and more, but also about how computers themselves work underneath the hood, memory and all. The course then transitions to Python, a higher-level language that you’ll understand all the more because of C. Toward term’s end, the course introduces SQL, via which you can store data in databases, along with HTML, CSS, and JavaScript, via which you can create web and mobile apps alike. Course culminates in a final project.
Course Contents
⌨️ Lecture 0 - Scratch
⌨️ Lecture 1 - C
⌨️ Lecture 2 - Arrays
⌨️ Lecture 3 - Algorithms
⌨️ Lecture 4 - Memory
⌨️ Lecture 5 - Data Structures
⌨️ Lecture 6 - Python
⌨️ Lecture 7 - SQL
⌨️ Lecture 8 - HTML, CSS, JavaScript
⌨️ Lecture 9 - Flask
⌨️ Lecture 10 - Emoji
⌨️ Cybersecurity
Links:
- https://cs50.harvard.edu/x
- https://www.youtube.com/watch?v=LfaMVlDaQ24
Navigational hashtags: #armknowledgesharing #armcourses
General hashtags: #cs #computerscience #harvard #algorithms #datastructures #datastructuresandalgorithms #python #sql #C #arrays
@data_science_weekly
This is CS50, Harvard University’s introduction to the intellectual enterprises of computer science and the art of programming, for concentrators and non-concentrators alike, with or without prior programming experience. (Two thirds of CS50 students have never taken CS before.) This course teaches you how to solve problems, both with and without code, with an emphasis on correctness, design, and style. Topics include computational thinking, abstraction, algorithms, data structures, and computer science more generally. Problem sets inspired by the arts, humanities, social sciences, and sciences. More than teach you how to program in one language, this course teaches you how to program fundamentally and how to teach yourself new languages ultimately. The course starts with a traditional but omnipresent language called C that underlies today’s newer languages, via which you’ll learn not only about functions, variables, conditionals, loops, and more, but also about how computers themselves work underneath the hood, memory and all. The course then transitions to Python, a higher-level language that you’ll understand all the more because of C. Toward term’s end, the course introduces SQL, via which you can store data in databases, along with HTML, CSS, and JavaScript, via which you can create web and mobile apps alike. Course culminates in a final project.
Course Contents
⌨️ Lecture 0 - Scratch
⌨️ Lecture 1 - C
⌨️ Lecture 2 - Arrays
⌨️ Lecture 3 - Algorithms
⌨️ Lecture 4 - Memory
⌨️ Lecture 5 - Data Structures
⌨️ Lecture 6 - Python
⌨️ Lecture 7 - SQL
⌨️ Lecture 8 - HTML, CSS, JavaScript
⌨️ Lecture 9 - Flask
⌨️ Lecture 10 - Emoji
⌨️ Cybersecurity
Links:
- https://cs50.harvard.edu/x
- https://www.youtube.com/watch?v=LfaMVlDaQ24
Navigational hashtags: #armknowledgesharing #armcourses
General hashtags: #cs #computerscience #harvard #algorithms #datastructures #datastructuresandalgorithms #python #sql #C #arrays
@data_science_weekly
Exceptional Resources for Data Science Interview Preparation. Part 1: Live Coding
In this article, we will understand what a live coding interview is and how to prepare for it.
This blog-post will primarily be useful to Data Scientists and ML engineers, while some sections, for example, Algorithms and Data Structures, will be suitable for all IT specialists who will have to go through the live coding section.
Table of contents
- Preparing for an Algorithmic Interview
- Resources
- Algorithms and Data Structures
- Programming in Python
- Solving a Practical Data Science Problem
- Hybrid
- Learning How to Learn
- Let’s sum it up
- What’s next?
NB:
I'm the author of the article.
It was initially published in Russian (on habr.com), then I added additional resources in English to make up for deleting resources in Russian language and published it on medium.com.
So, for Russian speakers I recommend to read Russian version, for English speakers I recommend to read English version and both will benefit from starring the repository, which will be maintained and updated when new resources become available.
Links:
- Medium (eng)
- Habr (rus)
Navigational hashtags: #armknowledgesharing #armarticles
General hashtags: #interview #interviewpreparation #livecoding #leetcode #algorithms #algorithmsdatastructures #datastructures #python #sql #kaggle
@data_science_weekly
In this article, we will understand what a live coding interview is and how to prepare for it.
This blog-post will primarily be useful to Data Scientists and ML engineers, while some sections, for example, Algorithms and Data Structures, will be suitable for all IT specialists who will have to go through the live coding section.
Table of contents
- Preparing for an Algorithmic Interview
- Resources
- Algorithms and Data Structures
- Programming in Python
- Solving a Practical Data Science Problem
- Hybrid
- Learning How to Learn
- Let’s sum it up
- What’s next?
NB:
I'm the author of the article.
It was initially published in Russian (on habr.com), then I added additional resources in English to make up for deleting resources in Russian language and published it on medium.com.
So, for Russian speakers I recommend to read Russian version, for English speakers I recommend to read English version and both will benefit from starring the repository, which will be maintained and updated when new resources become available.
Links:
- Medium (eng)
- Habr (rus)
Navigational hashtags: #armknowledgesharing #armarticles
General hashtags: #interview #interviewpreparation #livecoding #leetcode #algorithms #algorithmsdatastructures #datastructures #python #sql #kaggle
@data_science_weekly
Introduction To Algorithms by MIT
This is an introductory course covering elementary data structures (dynamic arrays, heaps, balanced binary search trees, hash tables) and algorithmic approaches to solve classical problems (sorting, graph searching, dynamic programming). Introduction to mathematical modeling of computational problems, as well as common algorithms, algorithmic paradigms, and data structures used to solve these problems. Emphasizes the relationship between algorithms and programming, and introduces basic performance measures and analysis techniques for these problems.
Link: Direct Link
Navigational hashtags: #armknowledgesharing #armcourses
General hashtags: #algorithms #datastructures #mit
@data_science_weekly
This is an introductory course covering elementary data structures (dynamic arrays, heaps, balanced binary search trees, hash tables) and algorithmic approaches to solve classical problems (sorting, graph searching, dynamic programming). Introduction to mathematical modeling of computational problems, as well as common algorithms, algorithmic paradigms, and data structures used to solve these problems. Emphasizes the relationship between algorithms and programming, and introduces basic performance measures and analysis techniques for these problems.
Link: Direct Link
Navigational hashtags: #armknowledgesharing #armcourses
General hashtags: #algorithms #datastructures #mit
@data_science_weekly