Mastering Probability and Statistics in Python

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 https://github.com/PacktPublishing/Mastering-Probability-and-Statistics…

Type
video
Category
Data
publication date
2021-06-28
what you will 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

duration
750
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
approach
This course is designed for beginners, although we will go deep gradually. You will learn theoretical concepts first, followed by its practical implementation in Python. At the end of each module, you will work on the homework/tasks, which will evaluate/further build your learning based on the previous concepts and methods.
audience
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.
meta description
A comprehensive course that teaches you the concepts and methodologies of statistics and probability with data science.
short description
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.
subtitle
Statistical and Probability foundations for ML: Statistics, Probability, and Bayes' Classifier
keywords
Probability and Statistics, Probability and Statistics in Python, Bayes’ theorem, Machine Learning, Data Science, Probability Theory, Probability Models
Product ISBN
9781801075091