Despite all the progress, a vast majority of the organizations are still reading & processing data in a more traditional “spreadsheet” way. However, for the past few years, Python has become the number 1 programming language for a vast range of applications. One industry where it has become the game-changer is data-related fields. All thanks to its simplicity & high readability, using Python for the data-related projects has become mandatory for everyone across the world.

 Considering its importance & the increase in the demand of Python-skilled individuals, we are launching this online course with the aim of teaching Statistics using Python 3.8. It is suitable for anyone who wants to enhance their programming skills while working on data. This course is packed with the crucial concepts including data visualization, random variables & distribution, linear regression models & much more.

 Ideal Audience

This course is suitable for:

1. Students or professionals looking to gain insights into Statistics & Python.
2. Anyone who wants to gain valuable skills for immediate implementation.

Why you should take this course?

It will be a perfect choice for anyone who wants to learn the practical application of statistics & Python from scratch. This course will provide a rich introduction to all the fundamentals & help you gain valuable exposure to easy-to-apply statistical concepts for real-world corporate problems.

 This course on statistics with Python will help you to learn statistical concepts like a random variable, frequency, distribution, population and sample, confidence interval, linear regression, etc. along with important Python library, data visualization & much more.

 This course includes:

1.   Intro to statistics & Python
2.  Data visualization
3.  Data analysis packages
4.  Random variables & distributions  
5. Sampling & inference
6. Linear regression models

Prerequisites

It will be a complete beginner guide & doesn’t require any prior knowledge of statistics or Python. However, a basic understanding of Python or the experience of working with data can be of great help.

What You Will Learn?

1. Statistics & Python
2. Importing & pre-processing data
3. Data visualization
4. Data manipulation
5. Sampling & inference
6. Recalling & applying important statistical concepts