Positional Encoding Courses and Certifications

Donato Capitella

The Transformer Architecture: Understanding Self-Attention and Positional Encoding

Delve into the revolutionary Transformer architecture, exploring self-attention mechanisms, positional encoding, and key components that revolutionized natural language processing and machine learning.

• YouTube
• 15 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

Deconstructing the Transformer Architecture

Master the Transformer architecture by building Multi-Head Attention, feed-forward networks, positional encodings, and complete encoder/decoder layers as reusable PyTorch modules from scratch.

• CodeSignal
• 4 hours
• On-Demand
• Free Certificate

Generative AI Language Modeling with Transformers

140 ratings at Coursera

Learn to apply transformer-based models for NLP tasks, covering encoder-decoder architectures, attention mechanisms, and implementations of BERT and GPT models using PyTorch for text classification and translation.

• Coursera
• 9 hours 18 minutes
• On-Demand
• Paid Course

Alberta Machine Intelligence Institute

Introduction to Generative AI: Concepts and Techniques

Discover Generative AI fundamentals, from Transformer architecture to practical LLM implementation, while mastering responsible AI practices and ethical considerations.

• Coursera
• 17 hours 6 minutes
• On-Demand
• Paid Course

Mastering Generative AI: Language Models with Transformers

Build job-ready skills in NLP based applications using GPT and BERT in just 2 weeks! Add sought-after skills employers are looking for to your resume and power up your AI career.

• edX
• 2 weeks, 3-5 hours a week
• On-Demand
• Free Online Course (Audit)

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 Mastery: LLMs Explained with Math (Transformers, Attention Mechanisms & More)

Unlock the mathematical foundations of transformers, attention mechanisms, and embeddings to master LLMs like GPT and BERT through hands-on implementation and vector mathematics.

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

Yannic Kilcher

Attention Is All You Need

Explore the groundbreaking Transformer architecture, revolutionizing sequence transduction with attention mechanisms. Learn its superior performance in machine translation and generalization to other NLP tasks.

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

Yannic Kilcher

NeRF - Representing Scenes as Neural Radiance Fields for View Synthesis

Explore NeRF, a neural network-based approach for 3D scene representation and novel view synthesis, achieving photorealistic results from sparse input images through volumetric rendering.

• YouTube
• 34 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

Aladdin Persson

NeRFs- Neural Radiance Fields - Paper Explained

1 review

Explore neural radiance fields for 3D scene representation and view synthesis, covering network architecture, key concepts, learning process, and advanced techniques.

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

Aleksa Gordić - The AI Epiphany

Attention Is All You Need - Transformer Paper Explained

Detailed walkthrough of the original transformer architecture, covering tokenization, embeddings, attention mechanisms, and decoding, with a focus on machine translation applications.

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

StatQuest with Josh Starmer

Transformer Neural Networks, ChatGPT's Foundation, Clearly Explained

Clear explanation of Transformer Neural Networks, the foundation of ChatGPT and modern AI. Covers key concepts like word embedding, self-attention, and encoder-decoder architecture.

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

Yannic Kilcher

Perceiver - General Perception with Iterative Attention

Explore DeepMind's Perceiver model, a versatile architecture that processes diverse input modalities using iterative attention, solving the quadratic bottleneck problem in Transformers.

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