U1: Introduction

• Presentation
• influences

U2: The basics of machine learning

• What is machine learning?
• Machine learning possibilities
• Configuration of the work environment

U3: your first models

• Types and examples of machine learning
• Data: the basis of any model
• Python libraries
• Your first model: linear regression
• Linear regression in detail

U4: Machine learning algorithms

• Sets and data analysis
• Linear regression exercise
• Logistic regression
• Logistic regression exercise
• decision trees
• Decision trees exercise

U5: More machine learning algorithms

• support vector machines
• Support vector machine exercise
• Clustering with K-means
• Clustering exercise with K-means

U6: Neural networks and deep learning

• Intuition and how neural networks learn
• Regression neural network
• Classification 1 neural network
• Classification Neural Network 2
• Convolutions and filters
• Convolutional Neural Networks 1
• Convolutional Neural Networks 2
• Learning Transfer 1
• Learning transfer 2

Final project

• Introduction to AI with Python