Coursera – Statistics with Python Specialization 2021-2

Description

Statistics with Python Specialization, the name of a practical and new-for-all statistics think tank, from Python to image storage, statistical inference, and more. and modeling, is used. This collection is for that which is designed for learners etc. basic and intermediate analysis concepts, statistical training using the Python programming language give. Learners that where data comes from and the types of data that can be collected will learn and continue design data, data management, and how to explore data and image storage to educate. Additionally, learners will be able to use the data to estimate and evaluate game theory, construction confidence interval, interpretation of inferential and implemented processing results, modeling, advanced statistical realization, and finally the importance and how to communicate. research questions with statistics and methods of analysis, given that they are taught to understand.

In the statistics collection with Python specialization, you will be able to:

Building and interpreting data visualization using Python programming language and related packages, books, house
Implementation and interpretation, processing and inferential statistics for the analysis of real data
Apply techniques, modeling, statistical data (regression, logic and linear model, linear model, multilevel and Bayesian inference techniques)
Understand the importance of relational issues, research method and data analysis

Specification volume:

Publisher: Coursera
Instructor: Brenda Gunderson, Brady T. West and Kerby Shed
French language
Learning level: introduction
Number of lessons: 3

Courses included in the Statistics with Python specialization bundle:

COURSE 1
Understanding and visualizing data with Python

COURSE 2
Inferential Statistical Analysis with Python

COURSE 3
Fit statistical models to data with Python

Prerequisite course:

High school level algebra is the only core knowledge required for the first course in the series. Basic training in Python and/or coding is recommended.