Beginner
ML Fundamentals
Master core machine learning concepts including supervised learning, model evaluation, and feature engineering. Build a strong foundation for advanced topics.
10-15 hours total12 modulesCertificate included
Course Modules
1
Types of Machine Learning
Supervised, unsupervised, and reinforcement learning overview
2
Supervised Learning Deep Dive
Classification and regression explained
3
Linear Regression
Understanding and implementing linear models
4
Logistic Regression
Binary and multiclass classification
5
Decision Trees
Tree-based models and information gain
6
Ensemble Methods
Random forests and gradient boosting
7
Unsupervised Learning
Clustering and dimensionality reduction
8
K-Means Clustering
Implementing and optimizing K-Means
9
Feature Engineering
Creating and selecting features
10
Model Evaluation Metrics
Accuracy, precision, recall, F1, ROC-AUC
11
Cross-Validation
K-fold and stratified validation
12
Hyperparameter Tuning
Grid search and random search