Thread by @AH_Merii

Want to become a Data Scientist? Here are some great resources that you should watch in order;Statistics & Linear Algebra Not Included 🧵
#100DaysOfCode #100DaysOfMLCode #DataScience #AI #MachineLearning #ArtificialIntelligence #ML #Coding #Coders #PyTorch #Tensorflow #Developer

Part 1 of Microsoft's Intro to Python Series:
Gets you up and running in python and introduces you to the basics of setting up your development environment.
youtube.com/playlist?list=…

Continuation of the series above.
youtube.com/playlist?list=…

After Completing the videos above, it's time to put what you learn into practice in a Notebook environment. There's no better place to do that than in #kaggle. Kaggle is a great place to find datasets and see what others have done with them. Applied Python
kaggle.com/learn/python

Next, and arguably the most important part of Data Science, is getting familiar with #Numpy and #Pandas. To do that we are going to be going through some of the courses on @dataquestio . Their courses are great and hands on.
dataquest.io/course/pandas-…

Okay so what now?? More Pandas, that's what! We continue with the hands on Kaggle course on pandas. You might have realized that their is a theme happening now. Practice! Practice! Practice! Repeat!

kaggle.com/learn/pandas

Next, we are going to start delving into the world of Machine Learning. Again the courses at Kaggle come to our aid, with their Intro to Machine Learning Tutorials!

kaggle.com/learn/intro-to…

What comes after intro? You guessed it! We are now going to go through the Intermediate Machine Learning Course, also on Kaggle!

kaggle.com/learn/intermed…

Okay so now we are getting comfortable manipulating our data, cleaning it, modelling. So what next? It's time for you to pick a small project and start it.

I hear you saying:
Where do I start? What project should I pick?

Up to you, that's for you to figure out!

Okay, so we finished our first project, we are now more comfortable coding. We started having a feel for the Data Science Workflow, what now?

Let's dive into the world of deep learning:

I can't recommend @AndrewYNg's course enough:
coursera.org/specialization…

You should now have a solid theoretical foundation for most of the deep learning concepts. But if after completing it you feel like you want some more practical knowledge. I highly recommend @deeplizard's youtube playlist Deep Learning with Pytroch
youtube.com/playlist?list=…

The course above will provide you with more familiarity with object oriented programming concepts and will give you a whole new perspective to working with deep learning frameworks.

Finally, Last but definitely not least, we have @jeremyphoward and @GuggerSylvain's Intro to Fast AI V2. Arguably the fastest (no pun intended) way to get into deep learning. You start with high level concepts and then dive into the nitty gritty details.
youtube.com/playlist?list=…

One more thing, you will feel overwhelmed, you will feel like you don't know anything? Keep pushing through! This feeling will slowly fade over time!💪💪💪

This is only the beginning, keep on learning! Did I miss anything?? If I did comment down below. #100DaysOfCode #AI #ML

Watch until video 36.

Watch until video 17.

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