PickAClass · AI, Tech & Engineering · Generative AI & Deep Learning

Transformer Architecture

Understand the fundamental deep learning architecture that powers modern AI. Learn about self-attention mechanisms, positional encodings, and the encoder-decoder structure that make models like GPT and BERT possible.

56 courses

Language Modeling with Transformers and Generative AI

Understand attention mechanisms, train BERT and GPT models for text generation, and explore modern retrieval-augmented generation concepts.

Foundations of Transformer Models and BERT

Master the core architecture behind modern language AI and learn how BERT processes complex text for real-world applications.

Fundamentals of Encoder-Decoder Architectures

Learn to build and train sequence-to-sequence models for translation, summarization, and text generation using modern machine learning principles.

Attention Mechanisms and Transformers for Beginners

Learn how neural networks prioritize information to power modern language translation, summarization, and generative AI models.

Foundations of Large Language Models: Building from Scratch with PyTorch

Understand the core mechanics of modern AI by learning how to implement transformer architectures and GPT-style models from the ground up using PyTorch.

Transformers from Scratch with PyTorch

Master the self-attention mechanism and build the foundational architecture behind modern AI, step by step.

Large Language Models: The Essential Foundations

Master the core mechanics of neural networks and large language models using PyTorch, designed for beginners wanting to understand modern AI systems.

Introduction to Deep Learning: Neural Networks, Vision, and Speech Systems

Build a solid foundation in artificial intelligence by understanding neural networks, computer vision, and speech recognition through clear, step-by-step written guides.

Introduction to Transformer Models and LLMs for NLP

Understand the core mechanics of BERT, GPT, and modern transformer architectures to build your foundational knowledge of natural language processing.

Understanding the Transformer Architecture: Build and Train NLP Models

Learn to implement self-attention mechanisms, assemble full transformer blocks, and train NLP models using Python and PyTorch through step-by-step written guides.

Encoder-Decoder Architectures for Sequence-to-Sequence Models

Master the foundational deep learning architecture behind machine translation, text summarization, and modern language technologies through clear written explanations.

Build Image Captioning Models

Develop the skills to create deep learning models that automatically generate descriptive captions for images.

Image Captioning Models: A Deep Learning Introduction

Develop foundational skills in deep learning to build artificial intelligence models that generate descriptive captions for images.

Build Deep Learning Image Captioning Models

Develop AI models that automatically generate descriptive text for images, applying foundational deep learning principles and modern architectures.

Image Captioning with Deep Learning

Learn to build AI models that automatically describe images in natural language, perfect for aspiring machine learning practitioners.

Understanding Encoder-Decoder Architectures in Machine Learning

Master the foundational sequence-to-sequence framework powering modern machine translation and generative language models through clear, written explanations.

Understanding Encoder-Decoder Architectures in Deep Learning

Learn the foundational neural network design behind language translation, sequence models, and attention mechanisms through clear, written explanations.

Introduction to Neural Machine Translation and Language Models

Build a solid foundation in neural language models and sequence-to-sequence architectures to understand how modern computer translation systems process human language.

Fundamentals of Encoder-Decoder Architecture

Master the core principles of Encoder-Decoder neural networks to build a strong foundation in sequence-to-sequence modeling for natural language processing and beyond.

Introduction to LSTM Networks and Sequence Training

Master the fundamentals of Long Short-Term Memory networks to build, train, and evaluate sequence-to-sequence models for time series and natural language processing.

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