Kappa
“Great things are not done by impulse, but by a series of small things brought together.”
Table of Contents
Fundamentals of AI
- Introduction to Machine Learning
- Mathematics Refresher for AI
- Supervised Learning Algorithms
- Linear Regression
- Logistic Regression
- Decision Trees
- Naive Bayes
- Support Vector Machines (SVMs)
- Unsupervised Learning Algorithms
- K-Means Clustering
- Principal Component Analysis (PCA)
- Anomaly Detection
- Reinforcement Learning Algorithms
- Q-Learning
- SARSA (State-Action-Reward-State-Action)
- Introduction to Deep Learning
- Perceptrons
- Neural Networks
- Convolutional Neural Networks
- Recurrent Neural Networks
- Introduction to Generative AI
- Large Language Models
- Diffusion Models
- Skills Assessment