Intro_to_supervised_learning

Course Outline

  1. Module 1: Introduction to Supervised Learning
  2. Module 2: Regression and KNN Models
  3. Module 3: Decision Trees and Random Forests
  4. Module 4: Optimization and Avoiding Overfitting

You Will Get

Basic Understanding of intro_to_supervised_learning

Certificate of Completion

Job Placement Assistance

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Introduction to Supervised Learning with Python

Learn how to build predictive models with supervised learning using Python

8.5 hours, 17 lessons

Instructed by Josef Macera

This Course is for you

Join our Python course today! Designed for beginners, our course will teach you the fundamentals of Python in a practical and engaging way. With the guidance of our experienced instructors and the support of a vibrant community, you'll develop the skills you need to pursue a career in tech.

What you will learn

Learn the basics of supervised learning and how it applies to the field of data science

Understand how to build and evaluate a predictive model

Master the use of popular Python libraries such as Scikit-Learn and Pandas for data analysis and model building

Explore different types of models such as regression, k-nearest neighbors, decision trees and random forests

Learn how to optimize a model and avoid overfitting

Discover how to work with real-world datasets and choose the best model for a given problem