Core Concepts:
Deep learning fundamentals including neural networks, CNNs, RNNs, and transformer-based models like BERT
Model version control and reproducibility using Git and DVC
Building and deploying AI applications using Flask and cloud platforms like AWS
Tools:
TensorFlow, PyTorch, BERT, Git, DVC, Flask, AWS (EC2/S3), Docker (optional)
Project:
Train a sentiment classifier using deep learning (e.g., BERT or RNN). Build a front-end interface with Flask and deploy the complete application on AWS. Ensure model versioning and reproducibility using Git and DVC.