If You Want A Radical Career Change,Â Expect To Do It All On Your Own But Don't Burn Your Bridges Immediately.Â *This article is mainly geared towards folks who want to learn more about data science with python on their own.*

## Why Data Science With Python?Â

Python is a general force in the programming language that is very effective for performing data science with plenty of resourcesÂ available from books to online courses. It has a significant setÂ of data science libraries one can use. It is a ready-to-use programming language with different packages for loading and playing around with data, visualizing the data, transforming inputs into a numerical matrix, or actual machine learning and assessment.

### CriticalÂ Skills in Python for Data ScienceÂ đ¤

If you want to learn data science with Python track, Here are five criticalÂ skills you need to develop as a beginner and to help you develop these skills, we have listed the best available resources in the following sections.

#### 1. Data Scraping

Gathering data from websites is one of the most logical and easily accessible sources of data. You'll need to learn how to use Python packages likeÂ Â urllib2,Â requests,Â simplejson,Â re,Â seleniumÂ andÂ beautiful soupÂ to make handling web requests and data formats easier.

#### 2. SQL

You need toÂ learn how to turn raw data into actionable insights and once you have a large amount of structured data, you will want to store and process it. To be an effective data scientist or an engineer, you should be able to wrangle and extract data from relational databases using SQL.

#### 3. Data Frames

SQL is important in data science and great for handling large amounts of data however it lacks Machine Learning and Data Visualization. So youÂ will have to go through the painfulÂ process of enabling Machine Learning services in SQL Server or use MapReduce to get data to a manageable size and then process it usingÂ Pandas.

#### 4. Machine Learning

A lot of data science can be done with select, join, and group by (or equivalently, map and reduce) but sometimes you need to do some non-trivial machine-learning. Before you jump into fancier algorithms, try out simpler algorithms likeÂ Naive BayesÂ andÂ regularizedÂ linear regression. In Python, these are implemented inÂ scikit-learn.

#### 5. Data Visualization

Data science is about communicating your findings, and data visualization is an incredibly valuable part of that. Python offers Matlab-like plotting viaÂ matplotlib, which is functional, even if it is ascetically lacking and if you are really serious about dynamic visualizations, tryÂ d3.

*Well Here's a Curriculum GuidelineÂ đ *

## Learn Data Science With PythonÂ ...

Python is a high-level programming language that is becoming more and more popular for doing Data Science and Machine Learning.Â Created by Guido van Rossum and first released in 1991, Python has a design philosophy that emphasizes code readability, notably using significant whitespace.Â 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.

### Python for Data Science CoursesÂ đ

Start with a Course or a book and study all the important topics for doing data science with Python. Our brain is similar to a muscle, Keeping your brain âfitâ with deliberate practice almost every day will help you find a sweet spot for Python.

#### Python For Everybody Specialization

*-*University of MichiganÂ#### IBM Python for Data Science

*-*IBM#### Introduction to Python for Data ScienceÂ

*-*Microsoft#### IBM Data Science Professional Certificate

*-*IBMÂ#### Python Programming Track - DataCamp

### ListenÂ To Python PodcastsÂ đŻ

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 greatÂ with consistently interesting guests who give away the best resources and present thoughtful content.

#### Talk Python to MeÂ (

*data-centric*)#### Podcast._init_

#### Test & Code

#### Python Bytes

### Networking for Nerds đ¤

If you are in the right group of people, you'll get the right kind of support. Find people who you could learn from and create some positive reinforcement. Here are some resources to help you get connected and understand your in-group.

The whole point of joining the online communities or going to conferences and regularly attending a Meetup is not to be liked but to benefit from the high-impact sessions and find someone who you will like because then they'll like you in return and help to you if you are seen around repeatedly.

#### PyData

#### reddit data science

#### Data Science Meetups

#### The Data Science Conference

#### KDNuggets Meetings

#### Machine Learning Meetups

If you don't find any Meetups around your area, write some Python code to find the right Meetup groups around your location. There is a Meetup API client written in Python with all the documentationÂ that has a complete list of available API methods and their descriptions.

## Get Good at Statistics and Maths for Data Science đ

It's easy to fall into a state of depression when you don't have theÂ ** know-how-to**Â of Statistics and Maths when learning Numpy, Pandas or Scikit-learn. We hope that the following resources will help you to start building the Data Science skills required today.

### Why 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.

#### Statistics for Data Science Courses

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

##### Introduction to Probability and Data - Duke University Â

##### Inferential StatisticsÂ - University of Amsterdam

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

##### Statistics Foundations: Understanding Probability and DistributionsÂ - Dmitri Nesteruk

##### MicroMasters Program in Statistics and Data ScienceÂ -Â Massachusetts Institute of Technology

If you already have a background in statistics and want to learn about the advanced statistical concepts, youâll find resources provided by EliteDataScienceÂ quite helpful.

### WhyÂ Learn Maths for Data Science

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.Â

#### Maths for Data Science CoursesÂ

You donât need a degree in Mathematics to succeed in data science. Yet, if you do have a math background, youâll 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 AlgebraÂ -Â SchoolYourself

##### Algebra IÂ - 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 SchoolÂ for an overview of mathematics that one should have been exposed to upon reaching Graduate School.

###### Before You Go

We have made sure that a team of 2 Python Programmers and 3 Content Researchers has put all the wisdom and experience in this article.Â We hope the resources listed in this articleÂ puts you in the fast lane and help you financially bootstrap your career in the field of Data Science with Python.

You may also be interested in reading aboutÂ The Best (and Affordable!!!) Data Science Courses with a Specialization Certificate.

If you liked this article enough, do share it with your friends and subscribe to our Data-Centric Newsletters to keep up with similar insights once every fortnight.Â Having said that â Is there anything you feel we should have included? **Let us know in the comments below**!

Wishing you the best with your career!Â *happy learning!* đđž