Recurrent Neural Networks (RNN) Courses and Certifications

Recurrent Neural Networks (RNNs) for Language Modeling with Keras

Learn how to use RNNs to classify text sentiment, generate sentences, and translate text between languages.

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

Introduction to Deep Learning

23 ratings

Deep Learning is subset of machine learning focused on extracting patterns from data using neural networks and use those patterns to inform the learning tasks.

• YouTube
• 2 days 7 hours 16 minutes
• Self-Paced
• Free Video

Packt

Advanced RNN Concepts and Projects

Master advanced RNN concepts, implement GRUs and LSTMs, and apply them to real-world projects like text generation and stock price prediction using TensorFlow.

• Coursera
• 6 hours 28 minutes
• Self-Paced
• Paid Course

Amazon;  Amazon Web Services;  Facebook Credential

Deep Learning

14 ratings

Master foundational deep learning topics, from neural networks to GANs. Build projects in PyTorch and explore cutting-edge AI applications in image processing, natural language, and generative models.

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

RNNs and Transformers

This course covers multiple RNN architectures and discusses design patterns for those models. You'll also learn about transformer architectures.

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

Serrano.Academy

A Friendly Introduction to Recurrent Neural Networks

2 ratings

Explore how computers predict and generate sequences using Recurrent Neural Networks. Learn about vectors, neural networks, and practical applications in cooking, weather, and more.

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

Alexander Amini;  MIT

MIT: Recurrent Neural Networks

2 ratings

Explore deep sequence modeling with recurrent neural networks, including LSTMs and attention mechanisms. Learn to tackle challenges like vanishing gradients and long-term dependencies in sequence tasks.

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

Brandon Rohrer

Recurrent Neural Networks and Long Short-Term Memory

1 rating

Explore recurrent neural networks and LSTM, their applications in sequence prediction, and practical uses in machine learning and AI.

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

Alexander Amini;  MIT

Recurrent Neural Networks and Transformers

Comprehensive exploration of recurrent neural networks, LSTMs, and attention mechanisms in deep learning, covering theory, implementation, and applications for sequence modeling tasks.

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

Alexander Amini;  MIT

MIT 6.S191 - Recurrent Neural Networks

Comprehensive lecture on Recurrent Neural Networks, covering theory, implementation, and applications. Explores sequence modeling, LSTM, attention mechanisms, and practical examples in deep learning.

• YouTube
• 1 hour 1 minute
• Self-Paced
• Free Video

Alexander Amini;  MIT

MIT 6.S191 - Recurrent Neural Networks

Explore recurrent neural networks, LSTMs, and attention mechanisms for sequence modeling. Learn backpropagation through time, gradient issues, and practical applications in deep learning.

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

Sequence Models

31244 ratings at Coursera

Master sequence models for NLP tasks, including RNNs, LSTMs, and transformers. Apply these techniques to speech recognition, language modeling, and machine translation.

• Coursera
• 1 day 13 hours 7 minutes
• Self-Paced
• Paid Course

Yannic Kilcher

Transformers Are RNNs- Fast Autoregressive Transformers With Linear Attention

Explore a novel approach to transformers using linear attention, reducing computational complexity and revealing connections to RNNs. Gain insights into faster, more efficient deep learning models for long sequences.

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

Credential

Deep Learning

147089 ratings at Coursera

Master neural networks, deep learning techniques, and their real-world applications. Build and optimize various architectures using Python and TensorFlow to tackle cutting-edge AI challenges in multiple domains.

• Coursera
• 12 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 5 courses

Pixel Recurrent Neural Networks

Explore cutting-edge image generation techniques, focusing on Pixel Recurrent Neural Networks. Learn about model architectures, RNN concepts, and LSTM equations for advanced AI applications.

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