Encoder-Decoder Architecture Courses and Certifications

Packt

Advanced Chatbots with Deep Learning and Python

Develop advanced chatbots using deep learning and Python. Learn architecture, implementation, and real-world applications in healthcare, business, and e-commerce. Build and deploy intelligent conversational AI systems.

• Coursera
• 3 hours 38 minutes
• Self-Paced
• Paid Course

Edureka

Transformer Architectures and Multimodal Models

Master transformer architectures from RNNs to multimodal systems, covering attention mechanisms, Vision Transformers, and scaling strategies for real-world NLP and AI applications.

• Coursera
• 11 hours 12 minutes
• Self-Paced
• Paid Course

Create Image Captioning Models

Close the gap between sight and description — create your own image captioning models using deep learning as you explore encoder-decoder architecture, model training, and evaluation.

• edX
• 2 hours
• Self-Paced
• Free Online Course (Audit)

Generative AI for Developers

1 rating

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
• Self-Paced
• Free Online Course

Create Image Captioning Models with Google Cloud

1 rating at Udacity

Master deep learning techniques to build models that automatically generate natural language descriptions for images using Google Cloud's encoder-decoder architecture.

• Udacity
• 1 hour
• Self-Paced
• Free Certificate

Aladdin Persson

Pytorch Transformers from Scratch - Attention Is All You Need

Implement Pytorch Transformers from scratch, exploring the "Attention is all you need" paper. Learn attention mechanisms, encoder-decoder architecture, and practical application.

• YouTube
• 57 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

Aladdin Persson

Pytorch Seq2Seq Tutorial for Machine Translation

Comprehensive tutorial on building a Seq2Seq model for German-English machine translation, covering implementation, training, and evaluation using PyTorch and the Multi30k dataset.

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

Google Cloud Tech

Creating Image Captioning Models: Overview and Components

Learn to build deep learning image captioning models, exploring encoder-decoder architecture, training techniques, and evaluation methods for accurate visual descriptions.

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

Neural Breakdown with AVB

Natural Language Processing Evolution: From Word2Vec and RNNs to GPT - 50 Key Concepts

Explore the evolution of Natural Language Processing through 50 key concepts, from fundamental Word2Vec and RNNs to modern transformer architectures and GPT models, with clear technical explanations.

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

Encoder-Decoder Architecture - Locales

This course, Encoder-Decoder Architecture - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Encoder-Decoder Architecture. This course gives you a synopsis of the encoder-decoder architecture, wh…

• Google Skills
• 8 hours
• No Longer Offered
• Free Online Course

Region Mutual Information Loss for Semantic Segmentation

1 rating

Explore advanced techniques in semantic segmentation, including region mutual information loss, à trous convolutions, and multi-scale features for improved image analysis and understanding.

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

Action Recognition, Temporal Localization and Detection in Videos

Explore action recognition, temporal localization, and detection in videos. Learn about knowledge transfer, 3D adaptations of object detection, and video segmentation techniques.

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

The Full Stack

Recurrent Neural Networks - Full Stack Deep Learning - Spring 2021

Explore Recurrent Neural Networks: architecture, challenges, solutions, and applications. Dive into LSTMs, bidirectionality, attention mechanisms, CTC loss, and non-recurrent sequence models like WaveNet.

• YouTube
• 1 hour 6 minutes
• Self-Paced
• Free Video