Build and optimize convolutional neural networks for advanced image classification tasks using TensorFlow and PyTorch.

Apply recurrent neural networks and LSTMs to sequential data problems, including time series forecasting and text autocompletion.

Develop neural language models and implement word embeddings for robust natural language processing.

Design and implement encoder-decoder architectures and Transformer models for machine translation and sequence-to-sequence tasks.

Master large language models and transformer architectures for advanced natural language processing applications.

Build and deploy multimodal networks that integrate multiple data types, such as text and images.

Implement multitask learning and solve advanced computer vision problems, including object detection and segmentation.

Apply ethical principles and practical strategies for tuning and deploying deep learning models in real-world settings.