# Download Udemy – Data Science & Python – Maths, models, Stats PLUS Case Study 2023-6

## Description

Data Science & Python course – Maths, models, Stats PLUS Case Study. Data science and Python course – Mathematical models of statistics plus case studies. What you will learn:

• Introduce the concept of data and information
• Identify the difference between business intelligence and data science
• Understanding and learning the data science process
• Defining the demands and challenges for people working in data science
• Identify the difference between the discussion of dispersion and descriptive and inferential statistics
• Learn to follow the steps after installing Anaconda
• Learn to expand the data discussion and interquartile range
• Define the advantages of obtaining conditional probability based on an example
• Identify the advantage of z-score calculation
• Learn p-value calculation and learning factors on p-value
• And…

Contents and overview

### What you will learn in Data Science & Python – Maths models Stats PLUS Case Study course

• Introduce the concept of data and information

• Identify the difference between business intelligence and data science

• Understanding and learning the data science process

• Define the demand and challenges for data scientists

• Identify the difference between the discussion of dispersion and descriptive and inferential statistics

• Learn the steps to follow after installing Anaconda

• Learn to expand the data discussion and interquartile range

• Define the advantages of obtaining conditional probability based on an example

• Identify the advantage of z-score calculation and other factors

• Learn how to calculate the p-value and learn other factors on the p-value

• Know the prerequisites and questions of a data scientist

• Learn the types of data acquisition

• Know the career aspects of a data scientist

• Discuss mathematical and statistical concepts and examples

• Learn descriptive and inferential statistics and their factors

• Learn how to use the Jupyter application

• Calculation of variance and discussion of other factors

• Get the conditional probability based on the example

• Learn what probability distribution and density are

• Learn the Z test and find the percentage under the curve

• Compare mean and variable

• Learn what the chi-square test is and discuss it based on the example data

• Teaching data preprocessing in Python

• Check array shape and dimensions and discussion in encoding window

• Learn why data visualization is important and how to use it

• Learn parametric and algorithmic methods

• Classification of learning and the concept of learning

• Learn K stands for Clustering and Algorithms

• Doing clustering and using sklearn on it and encoding other factors

• Learn TP, TN, FP and FN confusion matrix and discussion accuracy

• Training report classification and calculation in the coding window in Python

### This course is suitable for people who

• This course is for everyone interested in data science, machine learning, statistics, probabilities and business intelligence

### Data Science & Python course prerequisites – Maths models Stats PLUS Case Study

• No programming experience necessary, you will learn everything you need to know

### Installation guide

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