Sequence to Sequence Models Courses and Certifications

Toronto Machine Learning Series (TMLS)

Pre-Trained Multilingual Sequence to Sequence Models for NMT - Tips, Tricks and Challenges

Explore pre-trained multilingual sequence-to-sequence models for Neural Machine Translation. Learn adaptation techniques, training tips, and evaluation strategies while addressing challenges in implementation.

• YouTube
• 1 hour 30 minutes
• Self-Paced
• Free Video

UofU Data Science

Introduction to Machine Translation with Sequence-to-Sequence Models

Master sequence-to-sequence modeling fundamentals and applications in machine translation, focusing on neural network architectures and practical implementation techniques.

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

Creating Sequence Models and Transformers

Build sequence models from tokenization and embeddings through RNNs, attention, and transformers, culminating in a transformer-based Q&A system.

• Udacity
• 11 hours
• Self-Paced
• Paid Course

Deep Learning and NLP: Seq2Seq Model Theory + ChatGPT Prizes

4924 ratings at Udemy

Learn the Theory of Deep Natural Language Processing with the Seq2Seq model and enjoy several ChatGPT Prizes at the end!

• Udemy
• 8 hours 26 minutes
• Self-Paced
• Paid Course

Sequence Models

31293 ratings at Coursera

Build and train RNNs, GRUs, and LSTMs for character-level language modeling, word embeddings, attention mechanisms, and HuggingFace transformers applied to named entity recognition and question answering.

• Coursera
• 4 weeks, 9 hours a week
• Self-Paced
• Paid Course

Sequence Models & The Dawn of Attention

Build attention mechanisms from QKV tensors and masking, then implement reusable attention modules in PyTorch.

• CodeSignal
• 3 hours
• Self-Paced
• Free Certificate

Graham Neubig

CMU Advanced NLP 2021 - Conditional Generation

Advanced NLP lecture on conditional text generation, covering encoder-decoder models, search strategies, ensembling, and evaluation.

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

UofU Data Science

Introduction to Neural Machine Translation and Language Processing

Master the fundamentals of neural machine translation, from embedding matrices and RNNs to advanced concepts like teacher forcing, decoding methods, and BLEU score evaluation metrics.

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

Natural Language Processing with Sequence Models

1186 ratings at Coursera

Build sequence models for text: an RNN Shakespeare generator, GRU language model, LSTM named entity recognizer, and Siamese network for duplicate question detection.

• Coursera
• 3 weeks, 7 hours a week
• Self-Paced
• Paid Course

Natural Language Generation in Python

Imitate Shakespear, translate language and autocomplete sentences using Deep Learning in Python.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

UofU Data Science

Sequence-to-Sequence Models Through the Lens of Neural Machine Translation

Explore sequence-to-sequence models and neural machine translation fundamentals in this comprehensive data science presentation from University of Utah.

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

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
• Self-Paced
• 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
• Self-Paced
• Free Video

Deep Learning: Advanced Natural Language Processing and RNNs

7723 ratings at Udemy

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

• Udemy
• 8 hours 22 minutes
• Self-Paced
• Paid Course

Gen AI Foundational Models for NLP & Language Understanding

211 ratings at Coursera

Build NLP models in PyTorch: convert text with one-hot encoding, bag-of-words and Word2Vec embeddings, train N-gram language models, and implement sequence-to-sequence translation.

• Coursera
• 2 weeks, 5 hours a week
• Self-Paced
• Paid Course