1. State of the art of artificial intelligence
  2. Philosophy of artificial intelligence
  3. Future of artificial intelligence
  4. Project development process with artificial intelligence
  5. Data, your greatest asset

  1. Machine learning
  2. Deep learning
  3. Transformers
  4. Generation of synthetic data
  5. Hyperparameters in artificial intelligence models

  1. Linear regression
  2. Non-linear regression and support vector machines (SVM)
  3. Decision trees, random forests
  4. Fuse logic and gradient down
  5. Recommendation systems

  1. Preparation of the working environment: Anaconda, Visual Studio Code and Python
  2. Input dataset and data preprocessing
  3. TensorHub, TensorFlow and Keras
  4. Image processing
  5. Generation of artificial intelligence models

  1. Introduction
  2. Simple, multiple and logistic linear regression (I)
  3. Simple, multiple and logistic linear regression (II)
  4. Support vector machines (SVM)
  5. Decision trees

  1. KNN (k-nearest neighbors)
  2. Naive Bayes
  3. Evaluation of supervised models
  4. Example exercise
  5. Proposed exercise

  1. Introduction to clustering: purconsider and metrics
  2. K-means clustering
  3. Hierarchical clustering, other techniques and examples
  4. Principal component analysis (PCA)
  5. PCA example exercise

  1. Artificial Neural Networks (ANN) (I)
  2. Artificial Neural Networks (ANN) (II)
  3. Artificial Neural Networks (ANN) (III)
  4. Example exercise
  5. Proposed exercise

  1. Introduction
  2. Review: Artificial neural network (ANN)
  3. Review: ANN exercises
  4. Convolutional Neural Networks (CNN)
  5. CNN Exercises

  1. Natural language processing (I)
  2. Recurrent neural networks (RNN) (I)
  3. Recurrent neural networks (RNN) (II)
  4. Natural language processing (II)
  5. RNN Exercise

  1. Boltzmann Machines (BM)
  2. Restricted Boltzmann Machines (RBM)
  3. Recommender systems
  4. Recommender systems: metrics
  5. RBM exercise

  1. Self-organizing maps (SOM)
  2. SOM exercises
  3. Autoencoders (AE)
  4. AE exercises
  5. Proposed exercise