ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING
- Introduction to Digital Transformation: Definition and Brief History, Key Concepts, The Role of Digital Transformation in Today's World
- Introduction to the Concept of Smart Structures and Precision Instrumentation, Familiarization with Transformative Technologies: Artificial Intelligence and Machine Learning, Internet of Things (IoT), Big Data, Data Analysis, Blockchain, Cloud Computing
- Introduction to Artificial Intelligence and Its Relationship with Digital Transformation
- Challenges of Artificial Intelligence and Digital Transformation: Technical and Implementation Challenges, Ethical and Privacy Considerations, Economic and Social Impacts
- Basic Concepts of Machine Learning: Features, Optimization, Regression, Constraint Satisfaction Problems, Objective Function, Cost Function, Cost Function, Loss Function, Gradient Descent
- Familiarization with Classification and Clustering and Concepts of Supervised Learning (Different Types of Methods) and Unsupervised Learning ( Different Types of Methods), Reinforcement Learning
- Dataset Preparation: Data Preprocessing Techniques, Handling Imbalanced Data and Outliers, Overfitting and Underfitting
- Evaluation Metrics and Model Selection, Parameters and Hyperparameters
- Familiarization with Deep Learning and Its Various Algorithms: Deep Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Generative Adversarial Networks, Graph Neural Networks
- Development and Practical Implementation of AI Agents and Their Applications in Civil Engineering Courses