Machine Learning Fundamentals with Python
IntermediateAssumes foundational knowledge. Builds on basics.
Master machine learning from the ground up. Learn supervised and unsupervised learning, build models with scikit-learn, and understand the intuition behind algorithms like linear regression, decision trees, and neural networks. Hands-on Python exercises with real datasets.
Course Content
13 modules • 35 lessons
1
Course Introduction
1 lesson2
Module 1: What is Machine Learning?
3 lessons3
Module 2: Types of Machine Learning
3 lessons4
Module 3: Your ML Toolkit
3 lessons5
Module 4: Linear Regression
3 lessons6
Module 5: Classification Basics
3 lessons7
Module 6: Decision Trees and Random Forests
3 lessons8
Module 7: Model Evaluation and Metrics
3 lessons9
Module 8: Train/Test Splits and Cross-Validation
3 lessons10
Module 9: Feature Engineering Basics
3 lessons11
Module 10: Intro to Neural Networks
3 lessons12
Module 11: Capstone Project
3 lessons13
Course Conclusion
1 lesson
