Session 5: Recurrent Neural Networks (RNNs) (2 Hours)

• Introduction to RNNs, LSTMs, and GRUs
• Time-Series Forecasting & Text Generation

Hands-on Lab: Train an LSTM for Sentiment Analysis

Session 6: Transfer Learning & Fine-Tuning (2 Hours)

• What is Transfer Learning?
• Using Pre-Trained Models (VGG16, ResNet, Inception)

Hands-on Lab: Fine-Tune a Pre-Trained Model for Custom Image Classification

Session 7: Generative Models (2 Hours)

• Introduction to GANs (Generative Adversarial Networks)
• Generator vs. Discriminator Architecture

Hands-on Lab: Train a GAN for Image Generation

Session 8: Model Deployment & AI in Production (1 Hour)

• Model Optimization & Evaluation (Accuracy, Precision, Recall, F1 Score, ROC)
• Deploying Models using Flask & TensorFlow Serving

Hands-on Lab: Serve a Deep Learning Model via a REST API