USAAIO Foundations: Deep Learning, Transformers & PyTorch

🧠 Course Overview:

Welcome to USAAIO Foundations: Deep Learning, Transformers & PyTorch!
This course offers a comprehensive introduction to the core techniques driving today’s AI revolution. Centered on PyTorch, you will learn foundational concepts in deep learning, from basic neural networks to cutting-edge Transformer models, and explore practical applications in natural language processing, computer vision, and generative AI. Whether you’re a student or aspiring AI developer, this course will equip you with the theory, hands-on coding skills, and confidence to build modern AI systems.

🧩 What You Will Learn:

• PyTorch Basics: Tensors, operations, gradients, and building custom layers

• Multi-Layer Perceptrons (MLP): Activation functions, forward and backward propagation, and full model implementation

• Advanced Neural Network Layers: BatchNorm, Dropout, Softmax, Cross-Entropy loss, and their manual and PyTorch implementations

• Transformers: Attention mechanism (Q, K, V), positional encoding, multi-head attention, and Transformer encoder layers, with coding practice

• Applications of Transformers: NLP tokenization and embeddings, Vision Transformers (ViT), and optional Graph Neural Networks (GNNs)

• NLP Techniques: Pre-training (masked language models), fine-tuning, and Hugging Face basics

• Computer Vision & Generative AI: CNN architectures, object detection, UNet segmentation, autoencoders, GANs, and diffusion models (e.g., Stable Diffusion)

💻 Tools & Technologies:

• Programming Language: Python

• Deep Learning Framework: PyTorch

• Libraries: Hugging Face Transformers, NumPy, Pandas

• Projects & Practice: Custom layer implementations, Transformer coding from scratch, NLP and vision applications

🎓 Course Features:

• Hands-on Exercises: Implement neural network layers, Transformer components, and generative models with guided coding projects

• Theory + Practice: Manual derivations paired with PyTorch implementations for deep understanding

• Flexible Learning: Recorded lessons, downloadable code, and datasets

• Live Support: Instructor Q&A and discussion sessions

🎯 Ideal For:

• Students and professionals with basic Python skills eager to learn deep learning

• AI enthusiasts wanting to master PyTorch and modern architectures like Transformers

• Future AI engineers, data scientists, and researchers interested in NLP, vision, and generative AI

⏳ Duration:

10+ Weeks

• Weekly sessions (~1–2 hours each)

• Self-paced exercises and projects

📘 Prerequisites:

• Basic Python programming experience

• Familiarity with linear algebra and basic statistics recommended

📦 Materials Included:

• Video lectures and code walkthroughs

• PyTorch notebooks and datasets

• Additional reading materials and references

✅ Learning Outcomes:

By completing this course, you will be able to:

• Understand and implement fundamental and advanced deep learning models in PyTorch

• Build and train MLPs, Transformers, CNNs, and generative models

• Apply Transformer architectures to real NLP and vision tasks

• Gain hands-on experience with pre-training, fine-tuning, and Hugging Face tools

• Confidently explore state-of-the-art AI models and contribute to modern AI projects

🚀 Ready to Start?

Join USAAIO Foundations today and dive deep into the world of modern AI with PyTorch!