Python For Data Science

As we all know Python is a popular programming language and most of the people learning Python Programming Language now these days. According to TIOBE index Python is top 3rd among all programming languages. Python programming language is super easy to learn and widely used in various fields of industry. 

How do I Start Data Science in Python?

Python is a popular programming language for Data Science. Learning Data Science in Python Programming Language is super easy and fun. It is used by data scientist for various data science projects and application development because it provides great libraries and functionality to deals with Data Science Applications.

Start learning Data Science in Python Programming Language is easy and simple task. You just need to follow some steps, be consistent and determined to Master Data Science in Python Programming Language. Now, further in this article we are going to discuss Steps to Learn Data Science.

Image From Google

Why Is Python Good For Data Science?

Python is one of the best programming language for data science because it is easy to learn, more Scalable than R Programming Language and faster than MATLAB and STATA. It has great Data Science Community support where you can easily clarify you doubt. Python provides so many and great libraries for Data Science like Pandas, NumPy and Matplotlib. Due to these library support Graphics and Visualization of Bars, Charts and Histograms are super simple in Python.

What Are the Steps to Learn Data Science?

There are some steps that you need to follow to Master Data Science in Python Programming Language. These steps are given below :

1. Learn Python Programming Fundamentals and Basics

Python is open source, interpreted, high level language and object-oriented programming language. To became master in Data Science first you need to learn Python Programming Language fundamentals and basics. Learning Python fundamentals are super easy task. You can learn Python from a good video course, documentation or any other good resource.

2. Build Small Python Projects

Now you have already learn Python programming fundamentals. So it's time to do some hands on practice and build some cool projects. Building projects will help you learn faster, efficiently and give you in depth knowledge of Python basics. 

Projects that you can build to enhance your core concepts :

Beginner Level

i. Number Guessing
ii. Rock Paper Scissors
iii. Search Algorithms
1v. Website Blocker

Intermediate Level

i. Calculator
ii. Tic Tac Toe
ii. Web Scraping
iv. Currency Converter

3. Learn Data Science Libraries

After Doing all of this its time to learn about Data Science Libraries. There are so many libraries for different kind of work, but Numpy, Matplotlib and Pandas are most important libraries for Data Science. 

Libraries for Data Mining :- Scrapy , BeautifulSoup etc. 

Libraries For Data Visualization :- Matplotlib , Seaborn, Bokeh, Pydot, Plotly etc.

Libraries For Data Processing And Modeling :- NumPy, Pandas, Scipy, Keras, PyTorch, TensorFlow etc.

4. Build Data Science Project and Portfolio

After learning Data Science libraries like NumPy, Pandas and Matplotlib now you are ready to build some cool projects and boost your knowledge and experience. You can add all of these great projects into your Resume and Portfolio and showcase your work.

Projects that you can build with the help of these libraries

Beginner Level 

i.    Fake News Detection
ii.   Sentiment Analysis
iii.  Road Lane Line Detection
1v.  Color Detection With Python


Intermediate Level

i.    Speech Emotion Recognition
ii.   Diabetic Retinopathy
iii.  Gender And Age Detection
iv.   Chatbot

Advance Level

i.    Image Caption Generator
ii.   Movie Recommendation System
iii.  Credit Card Fraud Detection
iv.   Breast Cancer Classification

Now you just need to learn statistics and Data Visualization after that you know everything that is important to become a Data Scientist. As we all know 'Practice Makes A Man Perfect' so you just need to build a lot of projects to become more and more efficient.