If you are new to the world of Data Science and willing to give your career a bang on, we are here to assist. To start with,what Data Science programming language are you going to choose? Selecting the right programming language is imperative because it tells how easily and effectively you will master this Data Science field. 

Among two common and popular programming languages - R programming and Python programming, we would recommend you to go for the Python. The Python for Data Science is quite easy to read and understand and you can learn it without any hassles in a few days,unless or until you have someone who can guide you through the basics. 

You can also learn Python through an effective Data Science with Python online certification course.So, wait no more and get started with the easiest and convenient programming language - The Python.

Python facilitates the development of fundamentals of machine learning like linear regression and logistic regression.

Understanding Linear Regression

In the process of linear regression, the input data is studied and is used as training data to train the algorithm. This algorithm will actually predict the value of new data as per its training model. Pythons Visualization, Pandas library and model evaluation is used to create a machine learning model based on linear regression.

Understanding Logistic Regression

As a popular methodology to develop machine learning algorithms for deep learning and neural networks, logistic regression is used for more practical cases of machine learning.

It is more of a predictive algorithm. To begin with, developing logistic regression in Python one needs to make some assumptions like the dependent and independent variables. Remember you would need a lot of training data for Logistic Regression. The steps to be followed are

To build the logistic regression