This course provides a practical introduction to statistical analysis and machine learning with Python. Learn essential machine learning concepts, methods, and algorithms with a focus on applying them to solve real-world problems. 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!
Course Summary of Predictive Modeling with Python
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Skills You'll Learn
Data Analysis, Data Validation, Descriptive Statistics, Data Processing, Regression Analysis, Probability & Statistics, Statistical Hypothesis Testing, Machine Learning, Data Cleansing, Exploratory Data Analysis, Predictive Modeling, Probability Distribution, Feature Engineering, Statistical Inference, Statistical Analysis
From the lesson
Course Wrap-Up and Assessment
This module is designed to assess an individual on the various concepts and teachings covered in this course. Evaluate your knowledge with a comprehensive graded quiz on Probability, Statistical Modeling, and Machine Learning.
Taught By
Edureka