Attention Mechanisms Courses and Certifications

Attention Mechanism

50 ratings at Coursera

Explore the attention mechanism in neural networks, enhancing focus on specific input sequence parts for improved machine learning performance in translation, summarization, and more.

• Coursera
• 19 minutes
• Self-Paced
• Paid Course

Math Behind LLMs, Transformers and Modern Computer Vision

1087 ratings at Udemy

From Multi Head Attention and Embeddings to Transformers, Vision Transformers, Modern Image Segmentation + LLMs and SAM

• Udemy
• 6 hours 57 minutes
• Self-Paced
• Paid Course

PyTorch: Advanced Architectures and Deployment

18 ratings at Coursera

Master sophisticated PyTorch architectures from Siamese Networks to Transformers, plus deployment techniques including ONNX, pruning, and quantization for real-world applications.

• Coursera
• 1 day 6 hours 40 minutes
• Self-Paced
• Paid Course

Career Certificate

Generative AI Models and Transformer Networks Certification

14 ratings at Coursera

Master Generative AI from autoencoders to transformers. Build VAEs, GANs, and deploy GPT/BERT models with RAG techniques for real-world applications using TensorFlow.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 3 courses

Edureka

Generative AI and Prompt Engineering Essentials

12 ratings at Coursera

Master Generative AI and prompt engineering fundamentals through hands-on practice with GPT, BERT, and T5 models, learning advanced techniques for effective AI communication.

• Coursera
• 11 hours 37 minutes
• Self-Paced
• Paid Course

Career Certificate

Introduction to Transformer Models for NLP

5 ratings at Coursera

Master transformer architectures like BERT, GPT, and T5 through hands-on coding exercises. Build attention mechanisms, apply transfer learning, and fine-tune models for real-world NLP applications.

• Coursera
• 4 weeks, 5 hours/week
• Self-Paced
• Paid Course
• 3 courses

Generative AI: Foundations and Concepts

Explore the mathematical foundations of generative AI, from neural networks to advanced deep learning models, with practical implementation techniques and applications in engineering.

• Coursera
• 21 hours 36 minutes
• Self-Paced
• Paid Course

Edureka

Getting Started with Generative AI

Master foundational and advanced Generative AI concepts, from model architectures to deployment strategies, with hands-on experience in GANs, transformers, LLMs, and optimization techniques.

• Coursera
• 18 hours 57 minutes
• Self-Paced
• Paid Course

Edureka

Introduction to LLMs and Hugging Face

Discover transformer architecture, attention mechanisms, and Hugging Face tools to build intelligent language-driven systems with hands-on LLM fine-tuning and deployment.

• Coursera
• 10 hours 37 minutes
• Self-Paced
• Paid Course

Packt Career Certificate

AI Engineer Professional

Master advanced AI engineering through model optimization, deep learning architectures, transformers, and MLOps practices for production-ready solutions.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 3 courses

Quick Start Guide to Large Language Models (LLMs): Unit 1

Explore NLP evolution, master attention mechanisms, and build RAG systems using ChatGPT, Llama, and T5 while developing prompt engineering skills for effective LLM communication.

• Coursera
• 6 hours 18 minutes
• Self-Paced
• Paid Course

Edureka Career Certificate

Building LLMs with Hugging Face and LangChain

Master building production-ready LLM applications using Hugging Face and LangChain, from core concepts through optimization and deployment with modern MLOps practices.

• Coursera
• 8 weeks, 7 hours/week
• Self-Paced
• Paid Course
• 3 courses

Introduction to Transformer Models for NLP: Unit 1

Explore transformer architectures, attention mechanisms, and transfer learning with BERT and GPT models for advanced NLP applications using PyTorch.

• Coursera
• 3 hours 25 minutes
• Self-Paced
• Paid Course

Coursera Career Certificate

Transformers Unleashed: Master the Architecture of Modern AI

Master transformer-based AI systems—from building neural networks and NLP pipelines to deploying scalable ML models in cloud environments using TensorFlow, CI/CD workflows, and enterprise-grade architecture.

• Coursera
• 16 weeks, 4 hours/week
• Self-Paced
• Paid Course
• 6 courses

Edureka

Neural Models and Machine Translation

Discover neural architectures like RNNs, LSTMs, and Transformers to build powerful machine translation systems and NLP applications with hands-on fine-tuning exercises.

• Coursera
• 17 hours 8 minutes
• Self-Paced
• Paid Course