Udemy – Data Science Methods and Techniques [2025] 2024-7

In the Regression and Supervised Learning section, participants will be introduced to the fundamental and advanced concepts of regression, regression analysis, and prediction. This course provides the most comprehensive regression training package at the master’s level, covering practical theories, applications, and automated machine learning algorithms for model building, feature selection, and artificial intelligence. Topics range from linear regression models to advanced multivariate regression models. In the Classification and Supervised Learning section, the classification process, related theories, and visualization methods are explored. Applied classification models are also taught, including the powerful Ensemble Random Forest and Ensemble Voting Classifier models.

What you will learn

• Knowledge of data science methods, techniques, theory, best practices, and tasks
• Deep practical knowledge of data science and how to confidently manage common data science tasks
• Comprehensive and in-depth master’s level knowledge in the fields of regression, regression analysis, prediction, classification, supervised learning, clustering analysis, and unsupervised learning
• Working knowledge of Scikit-learn, Statsmodels, Matplotlib, Seaborn, and some other Python libraries
• Advanced knowledge of AI predictive models and automated model creation
• Cloud Computing: Using Anaconda Cloud Notebook (Cloud-based Jupyter Notebook) and learning to use cloud computing resources
• Option to use Anaconda Distribution (for Windows, Mac, Linux)
• Option to use Python environment basics with the Conda package management system and install/update libraries via the command line

This course is suitable for people who:

• Are interested in data science, regardless of whether they are a beginner or an expert.
• They want to master the fields of regression, prediction, classification, and clustering analysis.
• Are looking for a comprehensive and in-depth course on data science methods and techniques.
• Want to gain practical skills in using Python libraries for data science.
• They want to learn about AI predictive models and cloud computing.
• Regardless of whether they have a PhD or no education or experience, they can benefit from this course.

Installation Guide

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Subtitles: English

Quality: 720p