Course #1
ML Overview
A practical overview that shows how machine learning works, why it behaves that way, and how its structure supports real use.
3 Lessons6 Micro-lessonsDifficulty: Beginner
Course #2
Data Sets
Explore the world of data sets and understand their role in machine learning.
3 Lessons6 Micro-lessonsDifficulty: Beginner
Course #3
Features
Explore the role of features in machine learning models.
3 Lessons6 Micro-lessonsDifficulty: Beginner
Course #4
Labels
Understanding the role of labels in supervised learning and how they define outputs.
3 Lessons6 Micro-lessonsDifficulty: Beginner
Course #5
Training
Explore how machine learning models are trained to learn from data.
3 Lessons6 Micro-lessonsDifficulty: Beginner
Course #6
Regression
Explore the intricacies of regression in machine learning, focusing on predicting continuous values and refining predictive models.
3 Lessons6 Micro-lessonsDifficulty: Intermediate
Course #7
Classification
Explore the nuances of classification in machine learning, focusing on refining techniques and understanding failures.
3 Lessons6 Micro-lessonsDifficulty: Intermediate
Course #8
Clustering
Explore how clustering groups similar data points in machine learning.
3 Lessons6 Micro-lessonsDifficulty: Intermediate
Course #9
Model Tuning
Explore advanced techniques in tuning machine learning models for optimal performance.
3 Lessons6 Micro-lessonsDifficulty: Intermediate
Course #10
Cross Validation
Explore the intricacies of cross-validation in machine learning, focusing on refining model evaluation techniques.
3 Lessons6 Micro-lessonsDifficulty: Intermediate