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Data Science is intimidating and learning is exceedingly challenging without proper guidance.

If you want a radical career change, expect to do it all on your own.

Just bear in mind that you don’t burn your bridges immediately or else you will only give up learning.

In this piece, I want to provide some practical tips and resources about learning Data Science with Python on your own.

## Learn Data Science With Python ...

Python is a high-level programming language that is becoming more and more popular for doing Data Science and Machine Learning.

Created by Guido van Rossum and first released in 1991, Python has a design philosophy that emphasizes code readability, notably using significant whitespace.

Most coders prefer using Python for Data Science and developing artificial intelligence and machine learning apps.

In order to begin, you can download anaconda from field ion since it is highly recommended.

After downloading, you can start by comprehending the fundamentals of the Python, data scraping, importing data, data form.

Also, there is a need to learn Scientific libraries in Python such as Numpy, Matplotlib, Pandas, and SciPy,

We have listed some of the best (and free!!!) available resources in the following sections to help you bootstrap your career in the field of Data Science using Python.

### Why Data Science with Python?

Python is very effective for performing data science with plenty of resources available from books to online courses.

You will find significant set of data science libraries one can use with ready-to-use different packages for loading and playing around with data, visualizing the data, transforming inputs into a numerical matrix, or actual machine learning and assessment.

#### Also, Here’s a Curriculum Guideline

## Learning Data Science with Python

Start with any Python Course and learn all the important topics for doing data science with Python.

Remember that the brain is similar to any muscle, Keeping your brain “fit” with deliberate practice almost every day will help you find a sweet spot for Python.

I have a one recommendation for beginners and intermediate learners…

### Data Scientist with Python – Highly Recommended

This** Data Scientist with Python Career Track** is designed to take you from novice (i.e. almost no knowledge of programming) to “**Data Scientist”** over the course of 22 courses.

#### Is it right for you?

This learning track is suitable for beginners who’ve never touched Python, to get familiarized with the language and how Python can help in achieving data analysis tasks and become a reliable and skilled practitioner of the art.

##### GO TO CAREER TRACK

Here’s a very recent, helpful compilation of the Best Python for Data Science Courses from World-Class Educators.

## Navigate with these Python Podcasts

These podcasts will be of tremendous help while navigating through a forest of abstraction especially when you don’t know where you’re headed.

They are great with consistently interesting guests who give away the best resources and present thoughtful content.

## Get Good at Statistics for Data Science

A data scientist is someone who is better at statistics than any software engineer and better at software engineering than any statistician.

As a data scientist student, You can master the core concepts, probability, Bayesian thinking, and even statistical machine learning from best available books or an online course.

If you need an introduction to Statistics, start with any of the beginner level course listed below.

### Introduction to Probability and Data — Duke University

### Inferential Statistics — University of Amsterdam

### Bayesian Statistics: From Concept to Data Analysis — University of California

Try and integrate some of these online courses into your schedule while learning Python. You’ll feel very confident while learning to work with analytical libraries in Python.

If you want to learn the basics or want to get a refresher, I’ve got your covered in this piece about the Statistics for Data Science resources..

## Learn the Maths you’ve missed !!!

Mathematics is the bedrock of any contemporary discipline of science.

It is no surprise that almost all the techniques of modern data science (including all of the machine learning) have some deep mathematical underpinning or the other.

You don’t need a degree in Mathematics to succeed in data science. Yet, if you do have a math background, you’ll definitely get ahead.

Here are some best online classes to master the vocabulary, notation, concepts, and algebra rules that all data scientists must know before moving on to a more advanced material.

### Data Science Math Skills — Duke University

### Introduction to Mathematical Thinking —Stanford University

### Introduction to Algebra — SchoolYourself

Also, If you have little to no background in Maths or need a refresher, check this piece on Maths for Data Science and Machine Learning.

###### Thanks for making it to the end *;*)

If you like this article, I’ve got a few practical reads for you. One about **How to Learn** Data Science and one about The Best Data Science Courses.

I’ve also got this Data Science Newsletter that you might be into. I send a tiny email once or twice every quarter with some useful resource I’ve found.

Don’t worry, I hate spam as much as you. Feel free to subscribe. ☟

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