#Business intelligence training texas code

You will cover all the concepts of Logistic Regression in this module.Ī decision tree is a Supervised ML algorithm, which is used for both classification and regression problems. It is a simple classification algorithm where you can predict the categorical dependent variables with the assistance of independent variables. Logistic Regression is also one of the most popular supervised ML algorithms, like Linear Regression. This module will lecture you on identifying the significant differences between the means of two or more groups. You can split observed variance data into various other components for further analysis and tests using ANOVA. This module will give you a deeper understanding of Hypothesis Testing and Associated Errors.Ĭhi-Square is a Hypothesis testing method used in Statistics, where you can measure how a model compares to actual observed/surveyed data.Īnalysis of Variance, also known as ANOVA, is a statistical technique used in AI and ML. Hypothesis Testing is a necessary Statistical Learning procedure for doing experiments based on the observed/surveyed data. Hypothesis Testing and Associated errors.Sampling Distribution is statistical data acquired from numerous samples drawn from a specific population.Ĭentral Limit Theorem (CLT) is used to estimate a normal distribution. Sampling Distribution and Central Limit Theorem.You will also learn various types of Probability Distributions like Binomial, Poisson, and Normal Distribution.

This module will lecture you on Probability and Probability Distributions. Probability is a mathematical tool where you can study randomness, such as the likelihood of an event occurring in a random experiment.Ī statistical function where a random variable takes all the probable values and reports them within a specific range is called a Probability Distribution.

Probability and Probability Distributions.

This module will give you a deep understanding of exploring data sets using Matplotlib and Seaborn. Matplotlib is a library to create statically animated, interactive visualizations, whereas Seaborn is a Matplotlib based data visualization library in Python. This module will give you deep insights into EDA in Python and visualization tools. It allows us to uncover patterns and insights, often with visual methods, within data.

This module will give you a deep understanding of exploring data sets using Pandas and NumPy.Įxploratory Data Analysis, or EDA, is essentially a type of storytelling for statisticians. Pandas is a fast, powerful, flexible, and simple-to-use open-source library in Python to analyse and manipulate data. NumPy is a Python package for scientific computing like working with arrays, such as multidimensional array objects, derived objects (like masked arrays and matrices), etc.

#Business intelligence training texas code

In this module, you will work with Python syntax and execute your first code using vital Python fundamentals. It has a simple, easy-to-learn syntax that highlights code readability. Python is a high-level, interpreted programming language, which is widely used by many businesses across the globe.