Programming with Artificial Intelligence

TEACHING UNIT 1. MACHINE LEARNING Machine Learning Types of Machine Learning Machine Learning Algorithms and Models Evaluation Metrics in Machine Learning Regularization and Feature Selection in Machine Learning TEACHING UNIT 2. ARTIFICIAL NEURAL NETWORKS (ANN) Artificial Neural Networks (ANN) Structure and Architecture Activation Functions Training ANNs Convolutional Neural Networks (CNNs) and Their Applications Recurrent Neural Networks (RNNs) and Their Applications Generative Adversarial Networks (GANs) and Their Applications TEACHING UNIT 3. NATURAL LANGUAGE PROCESSING (NLP) Fundamentals of Natural Language Processing (NLP) Language Representation in NLP Feature Extraction in NLP Sequence-Based NLP Models NLP Models for Specific Tasks Applications of NLP TEACHING UNIT 4. COMPUTER VISION Computer Vision Image Preprocessing and Transformation Object Detection and Recognition Image Segmentation and Classification Applications of Computer Vision TEACHING UNIT 5. BIG DATA PROCESSING IN ARTIFICIAL INTELLIGENCE Big Data in Artificial Intelligence Distributed storage and processing Technologies and tools for Big Data processing Knowledge extraction from big data Machine learning in big data TEACHING UNIT 6. OPTIMIZATION AND TUNING OF AI MODELS Model evaluation and performance metrics Hyperparameter optimization Regularization and techniques for preventing overfitting Dimensionality reduction techniques Model tuning and ensemble methods LEARNING UNIT 7. REINFORCEMENT LEARNING Reinforcement learning Agents and Environments in Reinforcement Learning Reinforcement Learning Methods Exploration and Exploitation in Reinforcement Learning Applications of Reinforcement Learning LEARNING UNIT 8. DEPLOYMENT AND PRODUCTION OF AI MODELS Data Preparation for Model Deployment Design and Implementation of AI Services Monitoring and Evaluation of Models in Production Updating and Maintaining AI Models Scalability and Performance in AI Model Deployment