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Tom Mitchell Profile picture
@imtommitchell
Aug 5, 2023 • 7 tweets • 3 min read • Read on X
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GitHub offers the best free Data Science education on the internet.

But there are more than 372 million repositories to choose from.

How do you find the best ones?

Bookmark these 5 repositories and start learning fast:
1. Free Programming Books

Books are still an important source of knowledge for any field — and Data Science is no exception.

This GitHub repository contains a huge list of freely available books to learn anything related to programming.

🔗 https://t.co/VnC2HXnKAqgithub.com/EbookFoundatio…
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2. Data Science Roadmap

This repo covers everything from fundamentals to statistics and programming, and then on to machine learning, data visualization and beyond!

🔗 https://t.co/G0DTtEMCOzgithub.com/Moataz-Elmesma…
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3. Awesome Repo

The Awesome Github repository provides an organized list of machine learning libraries, frameworks and tools in many different languages.

🔗 https://t.co/nARAZNZgJAgithub.com/sindresorhus/a…
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4. Public APIs for Data

Finding datasets to practice on can be a challenge.

This repo contains a collective list of free APIs to use for data work

🔗 https://t.co/QSnYHkkAMLgithub.com/public-apis/pu…
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5. Project-Based Learning

A list of programming tutorials divided into primary programming languages like R and Python.

🔗 https://t.co/epotI5RLRxgithub.com/practical-tuto…
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And there you have it!

5 elite Github repos to get you started on your Data Science journey.

If you found this thread helpful, consider following me: @tommitchelldata

I post data-related content every day.

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More from @imtommitchell

Tom Mitchell Profile picture
Sep 22
The fastest way to learn Python when you already know SQL (in 6 steps):
1. Learn just enough basics (1 week max)

You need to understand:

Variables: name = "John"
Lists: [1, 2, 3]
Dictionaries: {"key": "value"}
Basic functions: len(), print()

Don't get stuck here.

You'll learn the rest naturally through pandas.
2. Jump straight into pandas DataFrames

DataFrames are SQL tables you can code with.

Everything you know about data structure applies here.

This is where SQL engineers have a massive advantage.
Read 11 tweets
Tom Mitchell Profile picture
Sep 20
I hear "you must learn SQL to become a data analyst" a lot.

And this is true.

But nobody tells you how to set it up and create your first table.

Here's how to do it in 4 simple steps :
1. Set up VSCode with SQLTools

Download VSCode from .

Open VSCode → Extensions (Cmd+Shift+X) → Search "SQLTools"

Install "SQLTools" by Matheus Teixeira.

Then install "SQLTools PostgreSQL".

These two extensions give you everything you need to get started: syntax highlighting, query execution, and database management.code.visualstudio.com
2. Install PostgreSQL

Option A: Homebrew (recommended) via terminal

brew install postgresql
brew services start postgresql

Option B: Direct download

Download from postgresql.org
Run the installer (accept defaults)
Remember your postgres password

Verify installation via terminal:

psql --version

You should see something like "psql (PostgreSQL) 15.4"
Read 8 tweets
Tom Mitchell Profile picture
Sep 10
The difference between SQL, NoSQL, MySQL, and Postgres explained in simple terms:
SQL (Structured Query Language) is the programming language used to manage and manipulate relational databases.
Before we get into the specifics, if you want to learn more about SQL, you should sign up for my (free) weekly newsletter The Data Dose.

I send 1 short, actionable email every week teaching 13,000+ professionals high paying data skills.

Check it out here:

Now, on with the breakdown...thedatadose.com
Read 11 tweets
Tom Mitchell Profile picture
Sep 3
I've worked with PowerBI for 6+ years.

Here are the 3 biggest mistakes I see beginners make (and how to avoid them):
1 - Not optimising data models

What's an easy way to kill user experience and force people to stop using your work?

Have a bloated, sluggish data model.

Instead, only select the data you need.

You can always add to it if needed.

Limit the amount of complex aggregations.

Need to include some complex operations?

Create tailored datasets beforehand.
2 - Cramming too much into visualisations

A simple trick here...

Got lots of categories?

Limit the number shown on each visualisation to top 3-5.

Make it easy for users to digest.

If you need to see the whole picture?

Group the values with least impact into "other".
Read 7 tweets
Tom Mitchell Profile picture
Aug 26
5 steps to write SQL queries that actually perform well:
1. Start with your WHERE clause

Why?

Because filtering early reduces the dataset size before expensive
operations like JOINs and GROUP BYs kick in.

Plan your filters first, then build around them.
2. Use Indexes

They help database find specific information much faster without having to search everything.

Pro tip: Composite indexes give you a huge benefit.

If you're regularly filtering on (date, status, region), create one index on all three columns in that order.
Read 9 tweets
Tom Mitchell Profile picture
Aug 25
If you want to work in data, you should know CI/CD.

Here's a dead simple breakdown that'll teach you fast:
What is CI/CD?

Continuous Integration (CI) + Continuous Deployment (CD).

In simple terms: automatically testing and deploying your data pipelines without breaking things.

Quality control for your code.
Why data teams need it:

Your SQL query works on your laptop.

But will it work in production?
Will it break when your teammate pushes code?
Will bad data crash your entire pipeline?

CI/CD prevents these disasters.

The 4 core components:
Read 12 tweets

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