Mastering Probability and Statistics in Python

Preview this course

This course is designed for beginners, although we will go deep gradually, and is a highly focused course designed to master your Python skills in probability and statistics, which covers the major part of machine learning or data science-related career opportunities.

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89 on-demand videos & exercises
Level: Beginner
12hrs 30mins
Access on mobile, web and TV

What to know about this course

In today’s ultra-competitive business universe, probability and statistics are the most important fields of study. That is because statistical research presents businesses with the data they need to make informed decisions in every business area, whether it is market research, product development, product launch timing, customer data analysis, sales forecast, or employee performance. But why do you need to master probability and statistics in Python? The answer is that an expert grip on the concepts of statistics and probability with data science will enable you to take your career to the next level. This course is designed carefully to reflect the most in-demand skills that will help you in understanding the concepts and methodology with regard to Python. The course is as follows: Easy to understand Expressive Comprehensive Practical with live coding About establishing links between probability and machine learning.

By the end of this course, you will be able to relate the concepts and theories in machine learning with probabilistic reasoning and understand the methodology of statistics and probability with data science, using real datasets. The code files and all related files are uploaded on the GitHub repository at

Who's this course for?

This course is for individuals who want to learn statistics and probability along with its implementation in realistic projects. Data scientists and business analysts and those who want to upgrade their data analysis skills will also get the benefit.

People who want to learn statistics and probability with real datasets in data science and are passionate about numbers and programming will get the most out of this course. No prior knowledge is needed. You start from the basics and gradually build your knowledge of the subject. A basic understanding of Python will be a plus but not mandatory.

What you'll learn

  • The importance of statistics and probability in data science.
  • The foundations for machine learning and its roots in probability theory.
  • The concepts of absolute beginning in-depth with examples in Python.
  • Practical explanation and live coding with Python.
  • Probabilistic view of modern machine learning.
  • Implementation of Bayes’ classifier on a real dataset.

Key Features

  • Easy explanations, yet complete and comprehensive course.
  • Fundamental, pythonic, and a complete course to master the important concepts used in data science.
  • Practical with live coding of the implementation of the concepts learned theoretically.

Course Curriculum

About the Author

AI Sciences 

AI Sciences are experts, PhDs, and artificial intelligence practitioners, including computer science, machine learning, and Statistics. Some work in big companies such as Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM.  AI sciences produce a series of courses dedicated to beginners and newcomers on techniques and methods of machine learning, statistics, artificial intelligence, and data science. They aim to help those who wish to understand techniques more easily and start with less theory and less extended reading. Today, they publish more comprehensive courses on specific topics for wider audiences.  Their courses have successfully helped more than 100,000 students master AI and data science.

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