Want to start with SQL? It can be your first step into the programming world!

Top resources for SQL! 🧵👇

You are looking to get into Machine Learning? You most certainly can
Because I believe that if an above-average student like me was able to do it, you all certainly can as well

Here's how I went from knowing nothing about programming to someone working in Data Science👇

The path that I took wasn't the most optimal way to get a good grip on Machine Learning because...

when I started out, I knew nobody that worked or had knowledge of Data Science which made me try all sorts of different things that were not actually necessary.

I studied C programming as my first language during my freshman year in college. And before the start of my second year, I started learning python just because I knew C is not the way to go.
I learned it out of curiosity and I had no idea about Machine Learning at this point.

I did not learn python by courses but by books. I'll link all the resources at the end.
The approach I took was just to make the same kind of programs I made in C but just replacing the syntax with that of python and practised those.
Already knowing a language made it easier.

For Machine Learning, the first thing that I did was to join Andrew NG's course which really hit it off for me
I didn't have to have any idea about Machine Learning for the course. I completed that in almost a month and it gave me a good intuition of things and the flow of ML.

I remember how hard it was to find resources for machine learning a couple of years ago.

Now we have so many of them, its impossible for you to not find what you're looking for.

Here are some of them 🧵

1️⃣ Kaggle

My go to place for finding datasets and code snippets, also a great place for discussions.

2️⃣ Papers with code

A collection of the latest and greatest research papers and the best part, a github repository with the code is included!

3️⃣ Kdnuggets

Guides, tutorials and articles on everything AI, Analytics, Big Data, Data Mining, Data Science, and Machine Learning.

4️⃣ Towards Data Science

A blog about data science with accessible and well written articles.

Practice and improve your HTML, CSS and JavaScript skills by building these 50 projects.

A thread 🧵

1. Expanding Cards
2. Progress Steps
3. Rotating Navigation
4. Hidden Search
5. Blurry Loading
6. Scroll Animation
7. Split Landing Page
8. Form Wave Animation
9. Sound Board
10. Dad Jokes App

11. Event KeyCodes
12. FAQ Collapse
13. Random Choice Picker
14. Animated Navigation
15. Incrementing Counter
16. Drink Water
17. Movie App
18. Background Slider
19. Theme Clock
20. Button Ripple Effect

21. Drag N Drop
22. Drawing App
23. Kinetic Loader
24. Content Placeholder
25. Sticky Navigation
26. Double Vertical Slider
27. Toast Notification
28. Github Profiles
29. Double Click Heart
30. Auto Text Effect

31. Password Generator
32. Good Cheap Fast
33. Notes App
34. Animated Countdown
35. Image Carousel
36. Hoverboard
37. Pokedex
38. Mobile Tab Navigation
39. Password Strength Background
40. 3D Boxes Background

"I want to learn how to code, but have no idea where to begin."

I've been getting this question pretty frequently lately, and thought it was a good time to put together a thread to cover all the basics.

And here it is!

Instead of just throwing a few links at you, I first want to cover something much more fundamental: The *reason* you want to learn to code.

I've had to train a good number of developers in my time. The ones that succeeded had rock-solid, persistent motivations. Is that you?

Some good motivations for learning how to code:

* Enabling a career change
* Insatiable curiosity, eagerness to learn
* Frustration with inefficiency + desire to improve things
* Larger goals in mind, coding being a stepping stone

Some bad motivations for learning how to code:

* It seems popular
* Your friends/family have ideas for apps
* You want to make lots of money by sitting in front of a computer
* You bought an expensive MacBook and are struggling to justify the expense

For those, trade forex.

Motivation matters, because of the one thing that's universally true about coding: It's hard.

Depending on what you do, you may have to learn several languages at once. Tools constantly update. New approaches land in the market on an annual basis. You're constantly upskilling.