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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
Jan 30
Nobody showed me how to create a data analysis portfolio.

I was lucky to land my first job.

If I were to start again, I'd create one using this 5-step plan: 👇
Step 1: Pick a subject that you are passionate about and enjoy.

You must have a genuine interest in the topic you are researching.

This will allow your mind to wander and be inquisitive, a key element in data analysis.
Step 2: Find some data and come up with questions to answer.

There are many amazing resources for finding data on the internet.

Two of my favourites are:

- Kaggle
- Google Datasets

Start to explore the data and come up with some questions.

If you struggle, ask ChatGPT.
Read 8 tweets
Tom Mitchell Profile picture
Jan 19
Pivot tables explained in simple terms:
Pivot tables are a way to interactively group, filter, and interrogate large amounts of data.

You might be thinking:

"But Tom. I can do all this in Excel anyway?"

But here's why they're so powerful...
Excel has a maximum row limit of 1.05m.

That means any dataset larger than that will have parts cut off.

A big problem if you're looking to produce accurate and reliable data insights.
Read 12 tweets
Tom Mitchell Profile picture
Nov 1, 2024
When I first started as a data analyst, I was dashboard crazy.

I quickly learnt the consequences of not validating my work properly during development.

Don't make the same mistake I did.

Instead, use this 4-step framework to bulletproof your work:
1. Verify data accuracy.

Ensure up-to-date data sources, accurate calculations, aggregations, and transformations in your visualisation tool.

Cross-check with original sources or validate samples to confirm accuracy.

This doesn't need to be complicated...

Do totals match up?

When you group by particular categories, does the segmentation work as expected?

Etc
2. Review visuals for accuracy and visual appeal.

Check data labels, legends, and axis scaling.

Does each visual give you enough info to extract insight?

Remember, you've probably looked at this for a while and got it; others will be seeing it for the first time.
Read 6 tweets
Tom Mitchell Profile picture
Oct 29, 2024
When starting out, a lot of people struggle with SQL joins.

The truth is, once you've grasped it, you won't forget it.

Here's my super simple breakdown of common SQL joins:
To start, let's quickly cover what a join is in SQL.

Data can be stored in RDMS, which means relational database management systems.

Being relational indicates data in tables can relate to each other.
To relate data, we need to join it.

When working with data, there are 2 types of joins that you will use more than any other.

Let's get into it...

For this post, let's pretend we have 2 tables: table 1 and table 2.
Read 7 tweets
Tom Mitchell Profile picture
Oct 28, 2024
How to write a killer data analyst resume with no experience:
Use functional/combination format to focus on skills & achievements, not work history.

Highlight your skills and accomplishments without emphasising the lack of work experience.

Focus more on what you can bring to the table rather than what you've done in the past.
Highlight education and relevant coursework.

Include degree, major, uni, and graduation year.

Mention data-related subjects to show theoretical knowledge.
Read 8 tweets
Tom Mitchell Profile picture
Oct 19, 2024
SQL is the undisputed champion of the data world.

To be successful in data, SQL skills are non-negotiable.

If you want to become a SQL champion, here's how to start: 👇
First things first, learn the basics of SQL.

Start by understanding the fundamental concepts of SQL, such as tables, queries, and basic syntax.

Familiarise yourself with commonly used SQL statements like SELECT, INSERT, UPDATE, and DELETE.
Next, set up a practice environment.

Create a sample database and tables to work with.

(Or you could use coding platforms like SQLPad or HackerRank.)

This will allow you to practice writing SQL queries and manipulating data.
Read 11 tweets

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