Transformers Courses and Certifications

Overview of Transformers - Stanford CS25: Lecture 1

Comprehensive introduction to NLP, Transformers, and AI agents, covering history, functionality, recent breakthroughs, applications, and challenges in the field of artificial intelligence.

• YouTube
• 1 hour 17 minutes
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• Free Video

Yannic Kilcher

Big Bird- Transformers for Longer Sequences

Explanation of BigBird's sparse attention mechanism for transformers, enabling longer sequence processing. Covers theoretical foundations, architecture details, and experimental results in NLP and genomics applications.

• YouTube
• 35 minutes
• On-Demand
• Free Video

AI Engineer

Going Beyond RAG - Extended Mind Transformers

Discover Extended Mind Transformers, a revolutionary approach that surpasses RAG by enabling models to dynamically select and attend to relevant information during generation.

• YouTube
• 16 minutes
• On-Demand
• Free Video

Alexander Amini

Recurrent Neural Networks, Transformers, and Attention - MIT 6.S191 Lecture 2

Dive into recurrent neural networks, transformers, and attention mechanisms with MIT's Introduction to Deep Learning lecture by Ava Amini.

• YouTube
• 1 hour 2 minutes
• On-Demand
• Free Video

Transformer Models with PyTorch

What makes LLMs tick? Discover how transformers revolutionized text modeling and kickstarted the generative AI boom.

• DataCamp
• 2 hours
• On-Demand
• Free Trial Available

CodeEmporium

Transformers - From Zero to Hero

Comprehensive deep dive into transformer architecture, covering key concepts from self-attention to tokenization. Includes hands-on coding for both encoder and decoder implementations.

• YouTube
• 3 hours 35 minutes
• On-Demand
• Free Video

James Briggs

Building MLM Training Input Pipeline - Transformers From Scratch

Learn to create a complex input pipeline for Masked Language Modeling, transforming raw OSCAR data into a DataLoader ready for training transformer models from scratch.

• YouTube
• 23 minutes
• On-Demand
• Free Video

James Briggs

Sentiment Analysis on Any Length of Text With Transformers - Python

Learn to perform sentiment analysis on long texts using transformers in Python, overcoming token limitations through chunking and processing techniques for NLP tasks.

• YouTube
• 27 minutes
• On-Demand
• Free Video

Alfredo Canziani

Differentiable Associative Memories, Attention, and Transformers

Explore differentiable associative memories, attention mechanisms, and transformers. Learn about energy minimization, planning, and various transformer applications in machine learning and AI.

• YouTube
• 2 hours
• On-Demand
• Free Video

Valence Labs

Transformers Meet Directed Graphs - Exploring Direction-Aware Positional Encodings

Explore direction-aware positional encodings for transformers on directed graphs, enhancing performance in code understanding and sorting network correctness testing.

• YouTube
• 1 hour 15 minutes
• On-Demand
• Free Video

MIT HAN Lab

Efficient Transformers - Lecture 20

Explore efficient transformer architectures for optimized deep learning on resource-constrained devices. Learn techniques to enhance performance and reduce computational demands.

• YouTube
• 1 hour 18 minutes
• On-Demand
• Free Video

MIT HAN Lab

Efficient Transformers - Lecture 20

Explore efficient transformer architectures for optimized deep learning on resource-constrained devices. Learn techniques to enhance performance and reduce computational demands.

• YouTube
• 1 hour 18 minutes
• On-Demand
• Free Video