Statistics & Mathematics for Data Science in Python

The must have foundational guide for all data science and machine learning developers

What you'll learn
Learn the foundational concepts of statistics and mathematics using Python
Learn how data science and machine learning work under the hood
Learn by implementing the abstract concepts

Requirements
Basic knowledge of Python will be needed to finish the course

Description
Master the Statistics & mathematics that powers Data Science!!

“Data Scientist is a person who is better at statistics than any programmer and better at programming than any statistician.” - Josh Wills

Data science is all about leveraging data to draw meaningful insights. And undoubtedly, converting raw and quantitative data into an organized form requires a lot of knowledge & hard work. When it comes to data science, mathematics & statistics are the 2 important pillars around which the majority of the concepts revolve.

Though expecting everyone to become the Aryabhatta can be wrong, but one can definitely dedicate some time to learn all the important concepts of Mathematics & Statistics to master Data Science, one of the most trending fields of this digital economy.

Considering the high demand for data scientists & all-time high skill gaps, we have curated this online course entirely dedicated to Statistics & Mathematics behind Data Science. All the covered concepts will aid you in identifying patterns from the data and help you to create algorithms.

Why you should learn Mathematics & Statistics for Data Science?

Maths & stats are the building blocks of data science

You will be able to create various algorithms

You can easily interpret data effectively

Helps in identifying & solving complex real-world problems

Model Selection based on their inherent limitations


Why you should take this course?

This course on statistics & mathematics is a perfect way of learning & understanding the important concepts involved in data science. You will learn all the maths & stats behind data science through its handcrafted sections in the most interactive way possible.

It covers everything from Vocabulary & Descriptive statistics to NLP along with all the important tools. In the end, a project is also included on data visualization & optimization to ensure complete learning.


This course includes:

Working with Google Colab

Vocabulary & descriptive statistics

Distribution types- Uniform, binomial, Poisson, normal & fitting

Inferential statistics with visualizations

Who this course is for:
Any one who wants to master the statistics and mathematics of Data science will find this course very useful

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