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
👍8
NeetCode: A better way to prepare for coding interviews
The best free resources for Coding Interviews. Period.
- Organized study plans and roadmaps (Blind 75, Neetcode 150).
- Detailed video explanations.
- Public Discord community with over 30,000 members.
- Sign in to save your progress.
Links:
- Roadmap
- Practice (Core Skills, Blind 75, Neetcode 150, Neetcode All)
- Algorithms and Data Structures for Beginners (course)
- Advanced Algorithms (course)
Navigational hashtags: #armknowledgesharing #armsites #armtutorials
General hashtags: #leetcode #python #algorithms #datastructures #interviewpreparation #technicalinterview
@data_science_weekly
The best free resources for Coding Interviews. Period.
- Organized study plans and roadmaps (Blind 75, Neetcode 150).
- Detailed video explanations.
- Public Discord community with over 30,000 members.
- Sign in to save your progress.
Links:
- Roadmap
- Practice (Core Skills, Blind 75, Neetcode 150, Neetcode All)
- Algorithms and Data Structures for Beginners (course)
paid- Advanced Algorithms (course)
paid Navigational hashtags: #armknowledgesharing #armsites #armtutorials
General hashtags: #leetcode #python #algorithms #datastructures #interviewpreparation #technicalinterview
@data_science_weekly
👍3
Competitive Programmer’s Handbook by Antti Laaksonen
The purpose of this book is to give you a thorough introduction to competitive programming. It is assumed that you already know the basics of programming, but no previous background in competitive programming is needed.
The book is especially intended for students who want to learn algorithms and possibly participate in the International Olympiad in Informatics (IOI) or in the International Collegiate Programming Contest (ICPC). Of course, the book is also suitable for anybody else interested in competitive programming.
It takes a long time to become a good competitive programmer, but it is also an opportunity to learn a lot. You can be sure that you will get a good general understanding of algorithms if you spend time reading the book, solving problems and taking part in contests.
Link: Book
Navigational hashtags: #armknowledgesharing #armbooks
General hashtags: #leetcode #programming #competitiveprogramming
@data_science_weekly
The purpose of this book is to give you a thorough introduction to competitive programming. It is assumed that you already know the basics of programming, but no previous background in competitive programming is needed.
The book is especially intended for students who want to learn algorithms and possibly participate in the International Olympiad in Informatics (IOI) or in the International Collegiate Programming Contest (ICPC). Of course, the book is also suitable for anybody else interested in competitive programming.
It takes a long time to become a good competitive programmer, but it is also an opportunity to learn a lot. You can be sure that you will get a good general understanding of algorithms if you spend time reading the book, solving problems and taking part in contests.
Link: Book
Navigational hashtags: #armknowledgesharing #armbooks
General hashtags: #leetcode #programming #competitiveprogramming
@data_science_weekly
👍2
Data Structures & Algorithms by Google
Familiarize yourself with common data structures and algorithms such as lists, trees, maps, graphs, Big-O analysis, and more!
Topics:
- Maps/Dictionaries
- Linked Lists
- Trees
- Stacks & Queues
- Heaps
- Graphs
- Runtime Analysis
- Searching & Sorting
- Recursion & DP
Link: Site
Navigational hashtags: #armknowledgesharing #armtutorials
General hashtags: #algorithms #leetcode #programming
@data_science_weekly
Familiarize yourself with common data structures and algorithms such as lists, trees, maps, graphs, Big-O analysis, and more!
Topics:
- Maps/Dictionaries
- Linked Lists
- Trees
- Stacks & Queues
- Heaps
- Graphs
- Runtime Analysis
- Searching & Sorting
- Recursion & DP
Link: Site
Navigational hashtags: #armknowledgesharing #armtutorials
General hashtags: #algorithms #leetcode #programming
@data_science_weekly
👍7
Grokking Algorithms. An illustrated guide for programmers and other curious people by Aditya Y. Bhargava
Grokking Algorithms is a friendly take on this core computer science topic. In it, you'll learn how to apply common algorithms to the practical programming problems you face every day.
You'll start with tasks like sorting and searching. As you build up your skills, you'll tackle more complex problems like data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python.
By the end of this book, you will have mastered widely applicable algorithms as well as how and when to use them.
Table of Contents:
1. Introduction to algorithms
2. Selection sort
3. Recursion
4. Quicksort
5. Hash tables
6. Breadth-first search
7. Dijkstras algorithm
8. Greedy algorithms
9. Dynamic programming
10. K-nearest neighbors
Link: Book
Navigational hashtags: #armknowledgesharing #armbooks
General hashtags: #algorithms #datastructures #leetcode
@data_science_weekly
Grokking Algorithms is a friendly take on this core computer science topic. In it, you'll learn how to apply common algorithms to the practical programming problems you face every day.
You'll start with tasks like sorting and searching. As you build up your skills, you'll tackle more complex problems like data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python.
By the end of this book, you will have mastered widely applicable algorithms as well as how and when to use them.
Table of Contents:
1. Introduction to algorithms
2. Selection sort
3. Recursion
4. Quicksort
5. Hash tables
6. Breadth-first search
7. Dijkstras algorithm
8. Greedy algorithms
9. Dynamic programming
10. K-nearest neighbors
Link: Book
Navigational hashtags: #armknowledgesharing #armbooks
General hashtags: #algorithms #datastructures #leetcode
@data_science_weekly
👍1