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    Henrik Johansson
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    Henrik Johansson's Master Regression & Prediction with Pandas and Python [2026] Course Review

    Community Insights

    Learn to Master Regression and Prediction with Pandas and Python for Data Science, Data Analysis, and Machine Learning

    Learning Format Online Course
    Subcategory Python

    Course Price $19.99

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    About Henrik Johansson

    Learn to Master Regression and Prediction with Pandas and Python for Data Science, Data Analysis, and Machine Learning

    Who Is Henrik Johansson?

    No bio available.

    Industry

    Development

    Total Students

    4,321 students

    Official Website

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    Experience

    Course Language

    English

    Social Channels

    Based in

    What Do You Learn in Henrik Johansson's Course?

    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
    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 D
    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

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