Name: Workshop: Fundamentals of Deep Learning (CNN, RNN, LLM)
Start: 2024-11-29T09:00:00+01:00
End: 2024-11-29T17:00:00+01:00
Location: MS Teams

Workshop: Fundamentals of Deep Learning (CNN, RNN, LLM)

Friday, November 29, 2024 - 9:00 AM

Monday, November 25, 2024
Tuesday, November 26, 2024
Wednesday, November 27, 2024
Thursday, November 28, 2024
Friday, November 29, 2024

9:00 AM Introduction (– Meet the instructor. – Get familiar with your GPU-accelerated interactive JupyterLab environment.)

9:00 AM - 9:30 AM

9:30 AM The Mechanics of Deep Learning (• Train your first computer vision model to learn the process of training. • Introduce convolutional neural networks to improve accuracy of predictions in vision applications. • Apply data augmentation to enhance a dataset and improve model generalization.)

9:30 AM - 12:30 PM

12:30 PM Lunch break
Lunch break
12:30 PM - 1:30 PM

1:30 PM Pre-trained Models and Large Language Models (Leverage pre-trained models to solve deep learning challenges quickly. Train recurrent neural networks on sequential data: • Integrate a pre-trained image classification model to create an automatic doggy door. • Leverage transfer learning to create a personalized doggy door that only lets in your dog. • Use a Large Language Model (LLM) to answer questions based on provided text.)

1:30 PM - 3:00 PM

3:00 PM Coffee break
Coffee break
3:00 PM - 3:15 PM

3:15 PM Final Project: Object Classification (Apply computer vision to create a model that distinguishes between fresh and rotten fruit: • Create and train a model that interprets color images. • Build a data generator to make the most out of small datasets. • Improve training speed by combining transfer learning and feature extraction. • Discuss advanced neural network architectures and recent areas of research where students can further improve their skills.)

3:15 PM - 4:15 PM

4:15 PM Final Review (– Complete the assessment to earn a certificate. – Review key learnings and wrap up questions. – Take the workshop survey.)

4:15 PM - 4:45 PM

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