Ementorhub

What you'll learn

Manage and preprocess data for statistical analysis and modeling.

Conduct hypothesis testing using advanced statistical techniques.

Build exploratory data analysis (EDA) models to uncover insights.

Build and evaluate models to solve real-world data challenges.

Skills you'll gain

Statistical Inference

Data Validation

Statistical Analysis

Data Cleansing

Machine Learning

Data Processing

Probability & Statistics

Regression Analysis

Statistical Hypothesis Testing

Exploratory Data Analysis

Data Analysis

Feature Engineering

Descriptive Statistics

Predictive Modeling

Probability Distribution

There are 6 modules in this course

By the end of the course, you will: - Understand different data types used in statistical analysis. - Learn techniques to manage inconsistent data effectively. - Perform hypothesis testing using parametric and non-parametric tests. - Develop exploratory data analysis (EDA) models using statistical and machine learning methods. - Enhance machine learning models through evaluation and optimization techniques. Designed for individuals with a foundational knowledge of Python programming and basic statistical concepts, this course is ideal for aspiring data analysts, data scientists, business executives, machine learning engineers, and anyone passionate about data-driven decision-making. Gain hands-on experience in statistical and predictive modeling and apply your skills to real-world scenarios. Enroll in "Predictive Modeling with Python" today and take your expertise to the next level!

Probability Distribution Function

Inferential Statistics

Introduction to (Exploratory Data Analysis) EDA

Predictive Modeling and Analysis

Course Wrap-Up and Assessment