Cheat Sheets for Data Science Interviews
Knowing the coding languages is the basis upon which all other parts of data science are built. Especially popular in the data science community is the holy trinity of coding languages:
-SQL
-Python
-R
1. SQL
The language specifically designed for querying databases, SQL is a champion when it comes to data extraction and manipulation.
Cheat sheet: SQL Basics Cheat Sheet
Link: https://learnsql.com/blog/sql-basics-cheat-sheet/
Cheat sheet: The Essential SQL Commands Cheat Sheet for Beginners
Link: https://itechbrand.com/the-essential-sql-commands-cheat-sheet-for-beginners/
This one simply lists the commands in SQL everybody needs.
Cheat sheet: SQL Cheat Sheet – Technical Concepts for the Job Interview
Link: https://www.stratascratch.com/blog/sql-cheat-sheet-technical-concepts-for-the-job-interview/
Python
Python is, for a reason, one of the most commonly used programming languages in data science.
Cheat sheet: Python Cheat Sheet
Link: https://websitesetup.org/python-cheat-sheet/
What you get: This very comprehensive yet very clear cheat sheet is perfect for anybody wanting to have a basis for starting working in Python.
Cheat sheet: Comprehensive Python Cheatsheet
Link: https://github.com/gto76/python-cheatsheet
R lang
The R programming language is a little less flexible than Python, so it’s not suitable for model deployment. It is created for statistical analysis and data visualization.
Cheat sheet: RStudio Cheatsheets
Link: https://www.rstudio.com/resources/cheatsheets/
Data Structures
Data scientists have to be familiar with data structures as a way of organizing and storing data. The chance is you won’t be using all the possible data structures all the time.
Cheat sheet: Data Structures Reference
Link: https://www.interviewcake.com/data-structures-reference
Cheat sheet: An Executable Data Structures Cheat Sheet for Interviews
Link: https://algodaily.com/lessons/an-executable-data-structures-cheat-sheet
#datascience #dsa #python #sql
@thegeeksnetwork
Knowing the coding languages is the basis upon which all other parts of data science are built. Especially popular in the data science community is the holy trinity of coding languages:
-SQL
-Python
-R
1. SQL
The language specifically designed for querying databases, SQL is a champion when it comes to data extraction and manipulation.
Cheat sheet: SQL Basics Cheat Sheet
Link: https://learnsql.com/blog/sql-basics-cheat-sheet/
Cheat sheet: The Essential SQL Commands Cheat Sheet for Beginners
Link: https://itechbrand.com/the-essential-sql-commands-cheat-sheet-for-beginners/
This one simply lists the commands in SQL everybody needs.
Cheat sheet: SQL Cheat Sheet – Technical Concepts for the Job Interview
Link: https://www.stratascratch.com/blog/sql-cheat-sheet-technical-concepts-for-the-job-interview/
Python
Python is, for a reason, one of the most commonly used programming languages in data science.
Cheat sheet: Python Cheat Sheet
Link: https://websitesetup.org/python-cheat-sheet/
What you get: This very comprehensive yet very clear cheat sheet is perfect for anybody wanting to have a basis for starting working in Python.
Cheat sheet: Comprehensive Python Cheatsheet
Link: https://github.com/gto76/python-cheatsheet
R lang
The R programming language is a little less flexible than Python, so it’s not suitable for model deployment. It is created for statistical analysis and data visualization.
Cheat sheet: RStudio Cheatsheets
Link: https://www.rstudio.com/resources/cheatsheets/
Data Structures
Data scientists have to be familiar with data structures as a way of organizing and storing data. The chance is you won’t be using all the possible data structures all the time.
Cheat sheet: Data Structures Reference
Link: https://www.interviewcake.com/data-structures-reference
Cheat sheet: An Executable Data Structures Cheat Sheet for Interviews
Link: https://algodaily.com/lessons/an-executable-data-structures-cheat-sheet
#datascience #dsa #python #sql
@thegeeksnetwork
LearnSQL.com
SQL Basics Cheat Sheet
SQL made simple: Download this beginner-friendly cheat sheet in A4, Letter, or mobile format. All the basics, syntax, and examples in one place.
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Answer: d
Explanation: For floating point literals, we have constant value to represent (10/0.0) infinity either positive or negative and also have NaN (not a number for undefined like 0/0.0), but for the integral type, we don’t have any constant that’s why we get an arithmetic exception.
Explanation: For floating point literals, we have constant value to represent (10/0.0) infinity either positive or negative and also have NaN (not a number for undefined like 0/0.0), but for the integral type, we don’t have any constant that’s why we get an arithmetic exception.
Angular — Micro-Frontend
Everything you need to know about microservice oriented architecture for the frontend from beginner to… - http://amp.gs/jlsRD
Everything you need to know about microservice oriented architecture for the frontend from beginner to… - http://amp.gs/jlsRD
Medium
Angular — Micro-Frontend
Everything you need to know about microservice oriented architecture for the frontend from beginner to advanced
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Learn how to code your own cloud deployment platform. If you've heard of Heroku before, that's essentially what you'll be building your own version of. This DevOps course will show you how to use the Flask Python framework – along with cloud engineering concepts and a tool called Pulumi – to get your cloud live. (80 minute YouTube course): https://www.freecodecamp.org/news/build-a-heroku-clone-provision-infrastructure-programmatically/
freeCodeCamp.org
Build a Heroku Clone – Provision Infrastructure Programmatically
Heroku is a platform as a service that enables developers to build, run, and operate applications entirely in the cloud. Heroku makes it simple to do things like create virtual machines to host applications and to deploy websites. Some of the featu...