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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 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.
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…
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
If you are looking for a Data Science Courses specifically, I’ve got you covered with this article about Best Data Science Courses on the Internet…
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 for 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 Mathematics for Data Science and Machine Learning.
Thanks for making it to the end
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