Sequence to Sequence Models Courses and Certifications

Deep Learning: Advanced Natural Language Processing and RNNs

7441 ratings at Udemy

Natural Language Processing (NLP) with Sequence-to-sequence (seq2seq), Attention, CNNs, RNNs, and Memory Networks!

• Udemy
• 8 hours 22 minutes
• On-Demand
• Paid Course

Stanford CS224N - Natural Language Processing with Deep Learning 2023

Master cutting-edge neural networks for NLP, from word vectors to Transformers, with hands-on tutorials covering RNNs, attention mechanisms, and modern language models.

• YouTube
• 1 day 5 hours 12 minutes
• On-Demand
• Free Video

Stanford CS224N - Natural Language Processing with Deep Learning - Winter 2021

Master neural networks, transformers, and attention mechanisms for text processing, translation, and language generation through Stanford's comprehensive deep learning approach.

• YouTube
• 1 day 7 hours 31 minutes
• On-Demand
• Free Video

Tensorflow 2.0 | Recurrent Neural Networks, LSTMs, GRUs

486 ratings at Udemy

Sequence prediction course that covers topics such as: RNN, LSTM, GRU, NLP, Seq2Seq, Attention, Time series prediction

• Udemy
• 1 hour 14 minutes
• On-Demand
• Free Online Course

Deep Learning for Natural Language Processing

Master neural networks for NLP, from feedforward and recurrent networks to transformers, transfer learning, and large language models, with practical implementation skills.

• Coursera
• 21 hours 3 minutes
• On-Demand
• Paid Course

Gen AI Foundational Models for NLP & Language Understanding

183 ratings at Coursera

Learn to implement, train, and evaluate generative AI models for NLP using PyTorch. Covers document classification, language modeling, translation, and building language models. Includes hands-on labs for practical application.

• Coursera
• 9 hours 57 minutes
• On-Demand
• Paid Course

Mastering Generative AI: Model Foundations and NLP

Gain job-ready skills in generative AI and NLP that employers need. Enhance your resume with in-demand expertise that will help you stand out as an AI engineer, AI developer, or data scientist.

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

International Centre for Theoretical Sciences

Sequence Alignment - Hidden Markov Models, Category Theory and All That Jazz by Soumyashant Nayak

Explore sequence alignment methods, from traditional algorithms to modern pseudo-alignment techniques, with insights on hidden Markov models and applications in RNA-Seq data analysis and evolutionary genetics.

• YouTube
• 1 hour 4 minutes
• On-Demand
• Free Video

Harvard CMSA

What Learning Algorithm is In-Context Learning? - Understanding Transformer Models and Neural Sequence Learning

Delve into the algorithmic foundations of in-context learning in transformers, exploring how neural networks implement implicit learning mechanisms through activation patterns and predictive modeling.

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

Discover AI

StreamingLLM: Enabling Infinite Sequence Length in Large Language Models

Dive into StreamingLLM's framework for extending LLM attention windows to handle infinite sequences, featuring practical implementation insights and code analysis.

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

Valence Labs

Structured State-Space Sequence Models for De Novo Drug Design

Explore the potential of Structured State-Space Sequence (S4) models in advancing chemical language modeling for de novo drug design, including bioactive compound identification and natural product design.

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

VinAI

Generative Sequence Models for Sequential Decision Making

Explore generative sequence models for decision-making under uncertainty. Learn how Transformer architecture and language modeling advances can enhance offline learning, online exploration, and multi-task generalization in AI.

• YouTube
• 1 hour 10 minutes
• On-Demand
• Free Video

Institut Henri Poincaré

Inferred Epistasis Enhances Neutral Models of Sequence Evolution

Explore how inferred epistasis improves neutral models of sequence evolution, enhancing understanding of evolutionary processes.

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

Center for Language & Speech Processing(CLSP), JHU

Low-resource Morphological Generation with Neural Sequence-to-Sequence Models

Explore neural sequence-to-sequence approaches for morphological generation in low-resource languages, including multi-task learning, cross-lingual transfer, and semi-supervised techniques.

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

Graham Neubig

Long Sequence Models in Advanced NLP - Lecture 13

Explore advanced techniques for handling long sequences in NLP, covering transformer architectures, model extrapolation, and evaluation methods for processing extended text contexts.

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