Fundamentals of Deep Learning Workshop
summary
Hands‑on workshop walks through building and training models from scratch with a first lab on MNIST handwriting digit classification, then explains training mechanics, CNNs for vision, LSTMs for text generation and transfer learning with pre‑trained models. Notebooks run in JupyterLab on GPU cloud (notably a Tesla T4 GPU (16 GB VRAM)) and include steps to clear GPU memory. Completion triggers an online assessment and an NVIDIA certificate; materials are downloadable for further work.
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chapters (13)
- 0:00Workshop introduction
- 2:20Setting up the environment
- 5:58Course outline
- 18:54Human vs. machine learning
- 22:34History of AI
- 26:11Neural network origins
- 29:46Expert systems
- 35:57Principles of deep learning
- 42:11The deep learning revolution
- 49:40Deep learning vs. programming
- 54:27Deep learning depth
- 56:58Practical applications of AI
- 1:05:54Hands-on lab session
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