Applied Artificial Intelligence

Catalog description

The course offers a comprehensive exploration of the capabilities and challenges of AI implementations, with a focus on strategies for designing and training efficient neural network architectures. Students will engage with the theoretical foundations of neural networks to understand their strengths and limitations, while also applying advanced frameworks such as Keras and TensorFlow to build and train models. Emphasis is placed on implementing state-of-the-art neural network architectures in complex, real-world contexts, requiring both critical analysis and technical proficiency.