10 Cheat Sheets You Need To Ace Data Science Interview by Abid Ali Awan via @kdnuggets

The only cheat you need for a job interview and data professional life. It includes SQL, web scraping, statistics, data wrangling and visualization, business intelligence, machine learning, deep learning, NLP, and super cheat sheets.

Useful to have and learn from even if it is NOT for an interview.

The Complete Data Science Study Roadmap by Nisha Arya via @kdnuggets

In this article, she is going to map out the things you need to do to become a Data Scientist. This article may solely be for beginners, however, there may be a thing or two that current Junior Data Scientists may have missed out on. This is where I am here to help fill in those gaps so that you don’t have to feel imposter syndrome or lack of confidence in your data science journey.

Interesting and as the introduction says, everyone can fill in gaps of knowledge from this roadmap.

Statistics and Probability for Data Science by Benjamin Obi Tayo, Ph.D. via @kdnuggets

In this article, he discusses the importance of statistics and probability in data science and machine learning.

This was really clear and easy to understand. It is pitched at a level that should appeal to folks are different levels of understanding.

“Semantic-free” is the future of Business Intelligence by Andrew Taft via @FlexItAnalytics

 Metrics and universal semantic layers enable semantic-free BI.

I found this very interesting and worth reading so you can think about the future.

21 Cheat Sheets for Data Science Interviews by Nate Rosidi by @kdnuggets

This article has researched and presents the best data science cheat sheets from around the internet, so you don’t have to do it yourself.

Very useful whether you are working as a Data Scientist already or not. Definitely some worth a bookmark, saving in Evernote or a printout.

Data Science Projects That Will Land You The Job in 2022 by Natassha Selvaraj via @kdnuggets

Project ideas and portfolio tips from a self-taught data scientist.

Some great ideas for you to prove that you know what you are talking about.

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101 DATA SCIENCE with Cheat Sheets (ML, DL, Scraping, Python, R, SQL, Maths & Statistics) by Anushka Bajpai via @Medium

Data Science is an ever-growing field, there are numerous tools & techniques to remember. It is not possible for anyone to remember all the functions, operations and formulas of each concept. That’s why we have cheat sheets and summaries. They help us access the most commonly needed reminders for making our Data Science journey fast and easy.

This is really like a one-stop-shop for cheatsheets - definitely worth a bookmark, a printout, adding to Evernote or whatever is your choice for preserving something important.

8 Free MIT Courses to Learn Data Science Online by Natassha Selvaraj via @kdnuggets

Create a data science learning path with courses from the world’s most prestigious university.

Some great courses from an amazing place,

Best Data Science Books for Beginners by Nisha Arya via @kdnuggets

The best knowledge is still placed in the libraries; within books. In this article, discover some of the top recommended Data Science books catering to beginners.

I would recommend the middle ground - do them both and read books while doing some targeted training too.

Get a Master's In Data Science for FREE! by Yash Gupta via @Medium

Education has been provided by schools and universities for a very long time. But in today’s digital era, there is nothing in this world you cannot learn using the Internet.

Some of the free online courses and sources of data are well worth the time investment in time and effort.

Data Science Programming Languages and When To Use Them by Nate Rosidi via @kdnuggets

Read this guide through the most common data science programming languages and when to use them in data science.

This is a great level of detail and very useful to use if you wonder if your choice was correct or if you should expand into another language.

Improve your Model Performance with Auto-Encoders by Satyam Kumar via @TDataScience

Use Autoencoders as a Feature Extractor.

This was really useful and could potentially save a lot of time and effort if you can get the balance right.

Everything About Python Set Data Structure: Beginner’s Guide — PyShark by Misha Sv via TDataScience

In this article we will focus on a complete walkthrough of a Python set data structure.

This is useful for beginners as well as anyone who feels that they need some kind of reminder on how it works.

10 Regression Metrics Data Scientist Must Know (Python-Sklearn Code Included) by T Z J Y via @Medium

A great article that definitely needs to be added to your notes and kept for reference. I've printed it and put it in a folder and also added it to my Evernote so I can refer back to it when needed.

5 Must-Know Terms in Time Series Analysis by @snr14 via @TDataScience

A fundamental part of data science.

This would a useful reminder/quick tutor in time series analysis. Make sure you also think hard about the method you want to use to plot this analysis as sometimes the graph or notation you use can help of hinder your understanding.

20 Python Libraries Every Data Scientist Use by Sara A. Metwalli via @Medium

Whether you're new to data science or not, you must be using some of these libraries.

I looked at this list and realised that there were some I had missed and that I could do some things in an easier/better way using a different library.

A Guide to 14 Different Data Science Jobs by Nate Rosidi via @kdnuggets

The field of data science is growing into one that features a variety of job titles This guide reviews different positions available for you to consider if you have a data science background.

Definitely worth a read as there are some great jobs out there that are NOT a data scientist but probably suit you and your skillset much better. I think I am closer to a data engineer a lot of the time, but not exclusively.

Visual Studio Code for Python and Data Science? Top 3 Plugins You Must Have by Dario Radečić via @TDataScience

Is it the best code editor for Python and Data Science?

Interesting - I had never thought of doing it that way.

8 Must-Have Git Commands for Data Scientists by @snr14 via @kdnuggets

Git is a must-have skill for data scientists. Maintaining your development work within a version control system is absolutely necessary to have a collaborative and productive working environment with your colleagues. This guide will quickly start you off in the right direction for contributing to an existing project at your organization.

I good quick reminder of the commands you need to use in Git - worth a printout or adding it to something like an Evernote folder.