UNIT 1. INTRODUCTION TO ARTIFICIAL INTELLIGENCE State of the art of artificial intelligence Philosophy of artificial intelligence Future of artificial intelligence Project development process with artificial intelligence Data, your greatest asset UNIT 2. TYPES OF ARTIFICIAL INTELLIGENCE Machine learning Deep learning Transformers Generation of synthetic data Hyperparameters in artificial intelligence models UNIT 3. INTRODUCTION TO MACHINE LEARNING ALGORITHMS Linear regression Non-linear regression and support vector machines (SVM) Decision trees, random forests Fuse logic and gradient down Recommendation systems UNIT 4. TURNKEY PROJECT Preparation of the working environment: Anaconda, Visual Studio Code and Python Input dataset and data preprocessing TensorHub, TensorFlow and Keras Image processing Generation of artificial intelligence models