# Just start

Sometimes I just felt silly trapped in the hole of *where to start* and I don't want others suffer the same. Life is too short and all you need is to learn from a good teacher and resource.

* If you want to learn Python, learn from [Corey Chafer](https://www.youtube.com/playlist?list=PL-osiE80TeTskrapNbzXhwoFUiLCjGgY7) or [Caleb Curry](https://www.youtube.com/playlist?list=PL_c9BZzLwBRLrHc6MntpdrNPKoC2tJr0z).
    
* If you want to learn about Scikit-learn, here is the [series](https://www.youtube.com/playlist?list=PL5-da3qGB5ID7YYAqireYEew2mWVvgmj6) from DataSchool.
    
* If you want to learn Deep Learning, learn from Jared Howard (fast-ai) [Series 1](https://www.youtube.com/playlist?list=PLfYUBJiXbdtS2UQRzyrxmyVHoGW0gmLSM), and [Series 2](https://www.youtube.com/playlist?list=PLfYUBJiXbdtTttBGq-u2zeY1OTjs5e-Ia)
    
* If you want to start a journey with **Pytorch**, learn from this [series](https://www.youtube.com/playlist?list=PLCC34OHNcOtpcgR9LEYSdi9r7XIbpkpK1). Good kickstart before rowing the boat yourself.
    
* If you want to start a journey with **Tensorflow**, learn from this [course](https://www.udemy.com/course/tensorflow-developer-certificate-machine-learning-zero-to-mastery/?couponCode=24T3MT53024). Worth every pennies, rich resources.
    
* If you want to start learning **Huggingface**, with all the big giga chad pretrained model, code along with this Transformers [docs](https://huggingface.co/docs/transformers/en/index) towards the end.
    
* If you want to learn [**FastAPI**](https://www.udemy.com/course/tensorflow-developer-certificate-machine-learning-zero-to-mastery/?couponCode=24T3MT53024), learn directly (do hands-on, don't copy) from the [docs](https://fastapi.tiangolo.com/learn/) written by Tiangolo.
    
* If you want to learn about Linux (though it *just to feel*), setup your laptop with WSL by following this [series](https://www.youtube.com/playlist?list=PLhfrWIlLOoKNMHhB39bh3XBpoLxV3f0V9) (pre-requisite before installing Docker).
    
* If you want to learn Docker, learn from this [page](https://docker-curriculum.com/). And checkout this useful [cheatsheet](https://dockerlabs.collabnix.com/docker/cheatsheet/) too.
    
* If you want to learn about SQL, but lazy to setup the workbench and server, just use [DuckDb with Python](https://duckdb.org/docs/api/python/overview.html).
    
* Or can just visit my [repo](https://github.com/Ammar-Azman/Data-Science-Materials) where I dumped all useful resources.