Master Regression & Prediction with Pandas and Python [2026] (Udemy.com)
Learn to Master Regression and Prediction with Pandas and Python for Data Science, Data Analysis, and Machine Learning
Created by: Henrik Johansson
Last updated September 2026
What you will learn
- Master Regression, Regression analysis, and Prediction both in theory and practice
- Master Regression models from simple Regression models to Polynomial Multiple Regression models and advanced Multivariate Polynomial Multiple Regression models
- Use Machine Learning Automatic Model Creation and Feature Selection
- Use Regularization of Regression models with Lasso Regression and Ridge Regression
- Use Decision Tree, Random Forest, XGBoost, and Voting Regression models
- Use Feedforward Multilayer Networks and Advanced Regression model Structures
- Use effective advanced Residual analysis and tools to judge models goodness-of-fit plus residual distributions
- Use the Statsmodels and Scikit-learn libraries for Regression supported by Matplotlib, Seaborn, Pandas, and Python
- Master Python 3 programming with Python’s native data structures, data transformers, functions, object orientation, and logic
How it compares
Against the other 461 rated Udemy courses in Data Science on CourseDuck:
- Rating4.8 out of 5higher than 94% of them
- Reviews883#162 of 462 by number of reviews
- Length42.5 hourslonger than 93% of them
- Last updatedSeptember 2026more recently than 90% of them
Course Description
Welcome to the course Master Regression & Prediction with Pandas and Python!
This three-in-one master class video course will teach you to master Regression, Prediction, Python 3, Pandas 2 + 3, and advanced Data Handling.
You will learn to master Regression, Regression analysis, and Prediction with a large number of advanced Regression techniques for purposes of Prediction and Automatic Model Creation, or so-called true machine intelligence or AI. You will learn to handle advanced model structures and eXtreme Gradient Boosting Regression for prediction tasks.
Python 3 is one of the most popular and useful programming languages in the world, and Pandas 2 and future version 3 is the most powerful, efficient, and useful Data Handling library in existence.
You will learn to master Python's native building blocks and powerful object-oriented programming. You will design your own advanced constructions of Python’s building blocks and execute detailed Data Handling tasks with Python.
You will learn to master the Pandas library and to use its powerful Data Handling techniques for advanced Data Science and Machine Learning Data Handling tasks. The Pandas library is a fast, powerful, flexible, and easy-to-use open-source data analysis and data manipulation tool, which is directly usable with the Python programming language.
You will learn to:
Master Regression, Regression analysis and Prediction both in theory and practice
Master Regression models from simple linear Regression models to Polynomial Multiple Regression models and advanced Multivariate Polynomial Multiple Regression models plus XGBoost Regression.
Use Machine Learning Automatic Model Creation and Feature Selection
Use Regularization of Regression models with Lasso Regression and Ridge Regression
Use Decision Tree, Random Forest, XGBoost, and Voting Regression models
Use Feedforward Multilayer Networks and Advanced Regression model Structures
Use effective advanced Residual analysis and tools to judge models goodness-of-fit plus residual distributions.
Use the Statsmodels and Scikit-learn libraries for Regression supported by Matplotlib, Seaborn, Pandas, and Python
Master Python 3 programming with Python’s native data structures, data transformers, functions, object orientation, and logic
Use and design advanced Python constructions and execute detailed Data Handling tasks with Python incl. File Handling
Use Python’s advanced object-oriented programming and make your own custom objects, functions and how to generalize functions
Manipulate data and use advanced multi-dimensional uneven data structures
Master the Pandas 2 and 3 library for Advanced Data Handling
Use the language and fundamental concepts of the Pandas library and to handle all aspects of creating, changing, modifying, and selecting Data from a Pandas DataFrame object
Use file handling with Pandas and how to combine Pandas DataFrames with Pandas concat, join, and merge functions/methods
Perform advanced data preparation including advanced model-based imputation of missing data and the scaling and standardizing of data
Make advanced data descriptions and statistics with Pandas. Rank, sort, cross-tabulate, pivot, melt, transpose, and group data
[Bonus] Make advanced Data Visualizations with Pandas, Matplotlib, and Seaborn
Cloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources.
Option: To use the Anaconda Distribution (for Windows, Mac, Linux)
Option: Use Python environment fundamentals with the Conda package management system and command line installing/updating of libraries and packages – golden nuggets to improve your quality of work life.
And much more…
This course is an excellent way to learn to master Regression, Prediction, Python, Pandas and Data Handling!
Regression and Prediction are the most important and used tools for modeling, AI, and forecasting. Data Handling is the process of making data useful and usable for regression, prediction, and data analysis.
Most Data Scientists and Machine Learning Engineers spends about 80% of their working efforts and time on Data Handling tasks. Being good at Python, Pandas, and Data Handling are extremely useful and time-saving skills that functions as a force multiplier for productivity.
This course is designed for everyone who wants to
learn to master Regression and Prediction
learn to Master Python 3 from scratch or the beginner level
learn to Master Python 3 and knows another programming language
reach the Master - intermediate Python programmer level as required by many advanced Udemy courses in Python, Data Science, or Machine Learning
learn to Master the Pandas library
learn Data Handling skills that work as a force multiplier and that they will have use of in their entire career
learn advanced Data Handling and improve their capabilities and productivity
Requirements:
Everyday experience using a computer with either Windows, MacOS, iOS, Android, ChromeOS, or Linux is recommended
Access to a computer with an internet connection
Programming experience is not needed and you will be taught everything you need
The course only uses costless software
Walk-you-through installation and setup videos for Cloud computing and Windows 10/11 is included
This course is the course we ourselves would want to be able to enroll in if we could time-travel and become new students. In our opinion, this course is the best course to learn to Master Regression, Prediction, Python, Pandas, and Data Handling.
Enroll now to receive 30+ hours of video tutorials with manually edited English captions, and a certificate of completion after completing the course!
Instructor Details
- 4.8 Rating
883 Reviews
Henrik Johansson
Henrik has a wide instructor/lecturer experience with more than 20 years in roles ranging from University teacher to sports coach to leadership roles in the private and public sectors.
Henrik has experience teaching students from all walks of life, from the poor to royalty, and has taught students from nearly all educational backgrounds, from high school to Ph.D.s.
Courses given by Henrik are intended to have unique content, and will teach you many new things.
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Reviews
By Kanaiyalal Patel on 11/8/2025
This is good and informative course. I was wondering if it also have some quizzes and practical practice labs and solutions that would be great, just my 2 cents.
By Timothy Watson on 3/20/2025
Wow! I thought I knew everything about regression and data science. I was mistaken. This course is great to achieve a modern and deeper understanding of regression and prediction theory. Thank you Henrik for creating this course!
By Ami Elaf Habib on 1/13/2025
Course content is very good and instructor is easy to follow. The course has advanced and free no-limits or "find the answer" challenges or exercises that make you concentrate, think, and get a deeper understanding of regression!
By Timothy P. Evans on 10/17/2024
Really good course! A very good mix of coding examples and practical advice about how to handle regression analysis situations. The automation part with machine intelligences building totally superior regression models is awesome.
By Kevin A. A. on 9/20/2024
This course is advanced and tough but the teacher is very good at explaining advanced regression concepts and models - without any hieroglyphic mathematics but with graphics and code. I recommend this course!
By Cecilia Innaress on 9/2/2024
Well-organized and good regression tutorials! The course covers unique content and goes in-depth into the technicalities and how-to of regression, prediction, data handling, pandas, and much, much more!
By John Wheeler on 9/1/2024
The course is well-structured and also useful for persons with a lot of knowledge in the domains of regression, modeling, or econometrics. The concepts are well-described and the code is well-structured.
By Glenn Lindsey on 6/3/2024
Challenging and good. More feedback at end of the course.
By Richard White on 5/5/2024
This is a fantastic course. The bundling with python and pandas is great - it connects everything and makes it so easy to check up data juggling and code, whenever needed for machine learning regression.
By Andrea M. on 5/2/2024
The content in this course is excellent and updated. There is a lot of useful stuff included and I learned lots of new things about regression and new tools like pandas. I recommend this course!
Quality Score
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Overall Score : 96 / 100
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