With hard work and determination, anyone can learn to code.

Here’s a list of my favorites resources if you’re learning to code in 2021.

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I've applied for a total of 10 development jobs in my life:

- 7 lead to interviews
- Of those 7, 4 was a good fit for me
- Of those 4, 3 offered me the job
- In all 3 cases, I negotiated a better deal

🧵 on what worked for me and what YOU can do to get similar results 👇

1. Apply for the RIGHT jobs. Look for midsize to large companies, not necessarily tech related. These tend to get way fewer applications than traditional tech companies, so it's easier to get your foot in the door - and they also tend to be great environments for learning.

2. Spend time on your application. Make sure your resumé and written application is tailored to the exact position. Recruiters or hiring managers can smell a copy/pasted resumé from miles away. Use as many words from the job spec in your application as possible.

3. Have a portfolio. Show off your skills and some personality on your website. This is a nobrainer for front-end devs, but it's true for other areas too. It's a great way to stand out over other candidates by actually *showing* the value you can create and your experience.

4. Establish personal contact. Send a quick message or make a phone call before applying. Just introduce yourself to the person in charge of hiring and ask a simple question. It's the best way I find to make them remember your application when you submit it.

In this thread, I will tell you how to learn python for data science in 1 hour 👇 1/N

It's not possible 2/N

It's not possible 3/N

It's not possible 4/N

It's not possible 5/N

These are the tools you will need for machine learning in Python.

🧵👇

Anaconda

When you work in python, you'll be working with several frameworks and many of them work only on specific versions of python.

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Now imagine downloading a new version of python and then installing it for every framework you want to work with 😬.

Meet Anaconda which allows you to run several versions of python. It comes pre-installed with several data science and machine learning frameworks.

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Pip-env is also a way of maintaining several versions of Python and comes pre installed with Python.
You can use pip env or Anaconda, whichever works for you.

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Jupyter Notebooks

Jupyter notebooks is an IDE just like VS code or Sublime. The special thing about jupyter is that you can parts of code in mini code editors called cells. This is great for prototyping and testing code.

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Are you planning to learning machine learning this year?

These are the Python frameworks you need to learn as an absolute beginner.

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It can be overwhelming seeing all the machine learning frameworks at once and not even knowing what they do.

I made this thread so that your machine learning journey becomes just a little bit easier.

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This thread will only focus on Python frameworks.

Why?
Because Python is the most common path into machine learning.

( If you have experience with any other language then learning Python will not be difficult at all. )

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Here's the entire list:

- Pandas
- Numpy
- Matplotlib
- TensorFlow
- PyTorch
- Keras
- Scikit Learn

Let's see what they do.

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You'll have to interact with csv files or databases on a regular basis to access data in machine learning, pandas helps you do just that.

The cool thing about Pandas is that it actually doesn't change the original data...

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