Self-Attention Courses and Certifications

Transformer Models and BERT Model

1 rating

Explore Transformer architecture, self-attention, and how BERT supports text classification, question answering, and natural language inference.

• Google Skills
• 30 minutes
• Self-Paced
• Free Online Course

Create a Large Language Model from Scratch with Python – Tutorial

Build a GPT-style large language model from scratch in Python, covering tokenization, PyTorch training, self-attention, transformer blocks, and text generation.

• freeCodeCamp
• 6 hours
• Self-Paced
• Free Video

Code Your Own Llama 4 LLM from Scratch - Full Course

Build a Llama 4–style language model from scratch by implementing tokenization, embeddings, self-attention, rotary positional embeddings, and feed-forward layers.

• freeCodeCamp
• 3 hours 29 minutes
• Self-Paced
• Free Video

LLM from Scratch Tutorial - Code and Train Qwen 3

Build and train Qwen 3 from scratch by coding its architecture, optimization, training loop, evaluation, and inference.

• freeCodeCamp
• 1 hour 3 minutes
• Self-Paced
• Free Video

Transformers that Transform Well Enough to Support Near-Shallow Architectures - Stanford CS25 Lecture

Explore precision language models for efficient training and hardware-based control systems. Learn about non-random parameter initializations and applications in resource-limited environments.

• YouTube
• 1 hour 20 minutes
• Self-Paced
• Free Video

Lennart Svensson

Introduction to Transformer Architecture - Complete Video Series

1 rating

Dive into transformer architecture fundamentals through self-attention, encoders, decoders, and applications in NLP tasks like translation and text generation.

• YouTube
• 1 hour 40 minutes
• Self-Paced
• Free Video

Aladdin Persson

Pytorch Transformers from Scratch - Attention Is All You Need

Read the original Transformer paper and implement its attention, encoder, and decoder architecture from scratch in PyTorch.

• YouTube
• 57 minutes
• Self-Paced
• Free Video

Jay Alammar

The Narrated Transformer Language Model

A visual introduction to how Transformer language models tokenize text, use self-attention and feed-forward networks, and generate words from probability scores.

• YouTube
• 30 minutes
• Self-Paced
• Free Video

CodeEmporium

Transformers from Scratch

Master transformer neural networks by building complete architecture from scratch, including attention mechanisms, encoders, decoders, and practical translation applications.

• YouTube
• 4 hours 25 minutes
• Self-Paced
• Free Video

Neural Breakdown with AVB

Attention to Transformers from Zero to Hero - Theory and Hands-on Projects

Master neural attention and transformers through hands-on projects covering NLP, computer vision, and speech modeling with theoretical foundations and practical implementations.

• YouTube
• 4 hours 28 minutes
• Self-Paced
• Free Video

Code With Aarohi

Transformers for Computer Vision

Explore how Transformer models revolutionize computer vision tasks through Vision Transformers, image classification, object detection, and hybrid architectures with hands-on PyTorch implementations.

• YouTube
• 3 hours 55 minutes
• Self-Paced
• Free Video

StatQuest with Josh Starmer

Transformer Neural Networks, ChatGPT's Foundation, Clearly Explained

A step-by-step walkthrough of how transformers turn word embeddings and positional information into generated tokens through self-attention and encoder-decoder attention.

• YouTube
• 36 minutes
• Self-Paced
• Free Video

Aleksa Gordić - The AI Epiphany

Attention Is All You Need - Transformer Paper Explained

A visual walkthrough of the original Transformer architecture, from tokenization and attention through training loss and autoregressive translation decoding.

• YouTube
• 39 minutes
• Self-Paced
• Free Video

Abhishek Thakur

Understanding BigBird - Transformers for Longer Sequences

Understand BigBird’s block-sparse attention, implementation, complexity, and use for processing longer sequences than BERT.

• YouTube
• 27 minutes
• Self-Paced
• Free Video

Aleksa Gordić - The AI Epiphany

Non-Parametric Transformers - Paper Explained

A deep dive into Non-Parametric Transformers, which use self-attention across datapoints for relational reasoning on tabular data.

• YouTube
• 46 minutes
• Self-Paced
• Free Video