Learn regression analysis with Python - linear, logistic, Cox, and more, all through hands-on projects and real-world data to build your job-ready from the ground up.
What you'll learn
Build and evaluate linear and multilinear regression models
Use Python for data exploration and visualization
Avoid common regression traps like overfitting and dummy variable bias
Analyze classification problems using logistic regression
Apply Cox regression to survival analysis problems
Use ChatGPT to assist with Python modeling tasks
Interpret regression outputs to drive business decisions
Complete real-world capstone projects for your portfolio
The title may say "introduction" in it, but this course goes beyond the basics to help you truly understand regression analysis!
If you're ready to stop guessing and start predicting, this course is for you. You'll dive into the most commonly used regression models in the data science world - linear, logistic, Cox, and logarithmic - learning not just the math, but how to actually apply them in Python.
We take a practical approach: real-world datasets, guided projects, and step-by-step explanations to help you build confidence with each concept. Along the way, you'll explore topics like feature selection, model bias, overfitting, survival analysis, and more.
Plus you'll apply your new skills with capstone projects that bring it all together, helping you showcase your skills and get job-ready in data analysis, data science, and machine learning.


https://rapidgator.net/file/a3941f599d310fd3409bfbd0b0158719/Introduction_to_Regression_Analysis.part2.rar.html
https://rapidgator.net/file/9a10210c26a2e9ae8e028ab7f65e3ee0/Introduction_to_Regression_Analysis.part1.rar.html