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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
25 min
2
Supervised Learning Deep Dive
Classification and regression explained
45 min
3
Linear Regression
Understanding and implementing linear models
40 min
4
Logistic Regression
Binary and multiclass classification
35 min
5
Decision Trees
Tree-based models and information gain
40 min
6
Ensemble Methods
Random forests and gradient boosting
50 min
7
Unsupervised Learning
Clustering and dimensionality reduction
45 min
8
K-Means Clustering
Implementing and optimizing K-Means
35 min
9
Feature Engineering
Creating and selecting features
50 min
10
Model Evaluation Metrics
Accuracy, precision, recall, F1, ROC-AUC
40 min
11
Cross-Validation
K-fold and stratified validation
30 min
12
Hyperparameter Tuning
Grid search and random search
45 min