Data Science is intimidating and If you want a radical career change, expect to do it all on your own. Just bear in mind that if you burn your bridges immediately, you will only inspire dread and 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.

### Check this (Python) Data Science Track – 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

If you are interested in finding about the Best Data Science Courses specifically, we’ve got you covered with the this article about Best (and Affordable…) Courses Data Science to Consider in 2019 …

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

### Statistics Foundations: Understanding Probability and Distributions – Dmitri Nesteruk

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 for Python.

If you want to learn about the advanced statistical concepts, you’ll find resources provided by EliteDataScience quite helpful.

## 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.

### Introduction to Mathematical Thinking – Stanford University

### Data Science Math Skills – Duke University

### Introduction to Algebra – SchoolYourself

### Algebra I – Khan Academy

Also, If you have little to no background in Maths or need a refresher, we suggest that get a copy of All the Mathematics You Missed: But Need to Know for Graduate School for an overview of mathematics that one should have been exposed to upon reaching Graduate School.

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

IcOne about the Best Data Science Courses and one about Data Science BootCamp with a Job Guarantee.

I’ve also got this Data-Centric 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.

Having said that – Is there anything you feel we should have included? **Let us know in the comments below**!

Wishing you the best with your career!

We hope the resources listed in this article puts you in the fast lane and help you bootstrap your career in the field of Data Science with Python.

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