Attention Mechanisms Courses and Certifications

3Blue1Brown

Neural Networks and Deep Learning Fundamentals

Discover neural networks fundamentals and backpropagation through visual explanations, plus explore transformers and LLMs that power modern AI applications.

• YouTube
• 3 hours 4 minutes
• On-Demand
• Free Video

Deep Learning for Natural Language Processing

2 reviews

This is an advanced course on natural language processing. Automatically processing natural language inputs and producing language outputs is a key component of Artificial General Intelligence.

• Independent
• On-Demand
• Free Online Course

LinkedIn AI Academy AI-100: 2 Supervised Learning with Neural Networks

170 ratings at LinkedIn Learning

Get a foundational understanding of neural networks from two LinkedIn AI engineers.

• LinkedIn Learning
• 1 hour 9 minutes
• On-Demand
• Free Trial Available

UofU Data Science

Attention Mechanisms in Deep Learning

Explore attention mechanisms in deep learning and neural networks through comprehensive theoretical foundations and practical implementations.

• YouTube
• 1 hour 22 minutes
• On-Demand
• Free Video

IIT Ropar;  NPTEL

Deep Learning - IIT Ropar

Explore deep learning architectures, optimization algorithms, and applications in computer vision and NLP. Gain practical knowledge for solving real-world problems using neural networks and advanced techniques.

• Swayam
• 12 weeks
• On-Demand
• Free Online Course

Deep Learning for Natural Language Processing

Master deep learning architectures and their NLP applications, from word embeddings to transformers, covering advanced topics like RLHF, PEFT, and large language models with hands-on tutorials.

• Swayam
• 12 weeks
• On-Demand
• Free Online Course

Building a Vision Transformer Model from Scratch with PyTorch

Build a Vision Transformer from scratch with PyTorch, implementing patch embedding through Transformer Encoder, and train your model on CIFAR-10 for practical image classification experience.

• freeCodeCamp
• 2 hours 5 minutes
• On-Demand
• Free Video

Evolution of the Transformer Architecture Used in LLMs (2017-2025) - Full Course

Explore the evolution of Transformer architecture in LLMs from 2017-2025, covering positional encoding, attention mechanisms, normalization methods, and activation functions with hands-on examples.

• freeCodeCamp
• 2 hours 50 minutes
• On-Demand
• Free Video

AI Engineering: Retrieval Augmented Generation (RAG) for LLMs

Master Retrieval Augmented Generation to build smarter AI systems using OpenAI APIs, FAISS, and advanced prompt engineering through hands-on projects and real-world applications.

• Zero To Mastery
• 20 hours
• On-Demand
• Paid Course

Code DeepSeek V3 From Scratch in Python - Full Course

Master the implementation of DeepSeek V3 from scratch with step-by-step Python coding instructions covering attention mechanisms, MLA, RoPE, KV Cache, MoE, and transformer blocks.

• freeCodeCamp
• 3 hours 47 minutes
• On-Demand
• Free Video

Code 7 Landmark NLP Papers in PyTorch - Full Neural Machine Translation Course

Dive into neural machine translation by replicating 7 landmark NLP papers in PyTorch, covering RNNs, LSTMs, attention mechanisms, and Transformers with hands-on coding labs.

• freeCodeCamp
• 7 hours 1 minute
• On-Demand
• Free Video

Generative AI for Developers

Dive into generative AI with a technical focus, covering diffusion models, attention mechanisms, transformers, BERT, image captioning, Vertex AI Studio, vector search, multimodal RAG, responsible AI, and MLOps.

• Google Skills
• 18-19 hours
• On-Demand
• Free Online Course

Alexander Amini;  MIT

MIT: Recurrent Neural Networks

2 reviews

Explore deep sequence modeling with recurrent neural networks, including LSTMs and attention mechanisms. Learn to tackle challenges like vanishing gradients and long-term dependencies in sequence tasks.

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

Transformers in Diffusion Models for Image Generation and Beyond

Explore how Transformers revolutionize diffusion models for image generation, covering UNet architectures, attention mechanisms, and cutting-edge techniques in synthetic media creation.

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

How I Learned to Stop Worrying and Love the Transformer - Stanford CS25 Lecture

Explore the Transformer's evolution and future directions with Ashish Vaswani, co-author of "Attention is All You Need". Gain insights into motivations, developments, and promising research areas in AI and NLP.

• YouTube
• 1 hour 21 minutes
• On-Demand
• Free Video