Applied Machine Learning: Supervised Learning
With Matt Harrison
Liked by 49 users
Duration: 2h 26m
Skill level: Intermediate
Released: 7/25/2025
Course details
Description
What is this course about?
In this course, Matt Harrison—a Python and data science corporate trainer, author, speaker, consultant, and advisor—shows you how to apply supervised learning techniques to real-world problems, focusing on both classification and regression tasks. Start with basic models like linear regression, and then advance to more complex algorithms like decision trees and XGBoost. Plus, explore model evaluation, optimization, and deployment techniques. With practical challenges and solutions, this course prepares you to apply supervised learning to solve problems in industries like healthcare, finance, and real estate.Objectives
What will I be able to do by the end of this course?
- Implement and evaluate both classification and regression models using supervised learning.
- Fine-tune and optimize machine learning models using cross-validation and hyperparameter tuning.
- Apply advanced techniques like ensemble methods (bagging and boosting) and XGBoost.
- Deploy a trained supervised learning model in a real-world application using Flask.
Audience
Who is this course for?
- Python developers
- Data scientists
- Machine learning enthusiasts
- Professionals keen on implementing supervised learning in real-world applications
Prerequisites
What do I need to know before taking this course?
- Basic knowledge of Python programming
- Familiarity with data analysis and statistics concepts
- Understanding of fundamental machine learning concepts is helpful
Skills you’ll gain
Earn a sharable certificate
Share what you’ve learned, and be a standout professional in your desired industry with a certificate showcasing your knowledge gained from the course.
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Showcase on your LinkedIn profile under “Licenses and Certificate” section
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Download or print out as PDF to share with others
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Share as image online to demonstrate your skill
Meet the instructor
Learner reviews
Contents
What’s included
- Learn on the go Access on tablet and phone
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