Build a Machine Learning Model with Python
Learn to build machine learning models with Python.
Includes Python 3, scikit-learn, matplotlib, pandas, Jupyter Notebooks, and more.
Skill level
IntermediateTime to complete
7 weeksCertificate of completion
YesPrerequisites
2 coursesWe suggest you complete the following courses before you get started with Build a Machine Learning Model with Python:- Getting Started with Python for Data Science
- Python for Data Science: Working with Data
About this skill path
More data is created and collected every day. Machine learning models can find patterns in big data to help us make data-driven decisions. In this skill path, you will learn to build machine learning models using regression, classification, and clustering methods. Along the way, you will create real-world projects to demonstrate your new skills.
Skills you'll gain
- Create neural nets from scratch
- Evaluate model performance
- Build supervised and unsupervised models
Syllabus
10 units • 16 lessons • 9 projects • 11 quizzes- 1
Introduction to Machine Learning
Welcome to the world of machine learning! You will learn some of the fundamental concepts behind machine learning.
- 2
Supervised Learning: Regression
Use linear regression or multiple linear regression to fit a line to data. Using this line, you can make predictions about future data.
- 3
Regression Cumulative Project
Practice your regression skills on a real-world dataset provided by Yelp!
- 4
Supervised Learning: Introduction to Classification
Learn to classify data using some of the most famous supervised machine learning models.
- 5
Supervised Learning: Advanced Classification
Learn some of the more complicated supervised machine learning models.
- 6
Supervised Machine Learning Cumulative Project
In this cumulative project, use your understanding of a variety of supervised machine learning models to analyze social media data.
- 7
Unsupervised Learning
Learn how unsupervised machine learning models work by implementing the K-Means clustering algorithm.
Hands-on learning
Don't just watch or read about someone else coding — write your own code live in our online, interactive platform. You'll even get AI-driven recommendations on what you need to review to help keep you on track.
Projects in this skill path
- Project
Honey Production
Fit a line to data about the honeybee population decline in the United States. - Project
Cancer Classifier
Classify tumors as either malignant or benign using K-Nearest Neighbors. - Project
Predict Titanic Survival
In this project you will use a Logistic Regression model to predict whether or not a passenger survived the sinking of the RMS Titanic.
Reviews from learners
- The progress I have made since starting to use codecademy is immense! I can study for short periods or long periods at my own convenience - mostly late in the evenings.ChrisCodecademy Learner @ USA
- I felt like I learned months in a week. I love how Codecademy uses learning by practice and gives great challenges to help the learner to understand a new concept and subject.RodrigoCodecademy Learner @ UK
- Brilliant learning experience. Very interactive. Literally a game changer if you're learning on your own.John-AndrewCodecademy Learner @ USA
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Related resources
- Article
What is Scikit-Learn?
Open-source ML library for Python. Built on NumPy, SciPy, and Matplotlib. - Article
Regression vs. Classification
Learn about the two types of Supervised Learning algorithms. - Article
Introduction to Regression Analysis
This article is a brief introduction to the formal theory (otherwise known as Math) behind regression analysis.
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Practice Projects
Guided projects that help you solidify the skills and concepts you're learning.Assessments
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