Data science with probability & statistics

Prerequisite for the course

  • There is no prerequisite for taking this training.Basic knowledge of any programming language will be beneficial


What if You miss a  class?

You can access recording video of to your missed class on our website.

Can i attend a demo class before enrollment?

You can view our live-demo  session recordings always.

Who should go for this Training?

This training of qwikmind is suited for all the professional which will be provided by trained IT professional.

What if I have more queries?

Write to us at with your query and we will get back to you soon.

About The Course

  • Its a detailed training program on data science statitics and probability which will be provided to you by our professional IT trainers.

  • You will learn here detailed side-by-side view of data science statitics and probability an e.d you will  get a clear idea about the places of implementation of these.

Why This Course

  • Data science team brings together three things: statistics, programming, and product knowledge.

  • Probability deals with predicting the likelihood of future events, while statistics involves the analysis of the frequency of past events

  • Average salary for a data scientist is $118,709 versus $64,537 for a skilled programmer. 

Course Description

  • Statistics plays and probability a central role in the data science approach. 

  • Data science is the develop edition of statistics and mathematics, combined with programming and business logic.Statistics is a crucial component of data science 

What you will learn

  • Core Statistics Concepts. Descriptive statistics, distributions, hypothesis testing, and regression.

  • Bayesian Thinking. Conditional probability, priors, posteriors, and maximum likelihood.

  • Intro to Statistical Machine Learning

Course Contents

  • Learn fundamentals of probability and statistics.

  • Learn  statistics, inferential statistics, and probability theory

  • Programming, statistics, the data science process, data visualization, and machine learning