Long short-term memory (LSTM) Courses and Certifications

Deep Learning Frameworks and Neural Networks Simplified

Master advanced deep learning skills with TensorFlow, Keras, and neural networks. Build cutting-edge AI models, implement RNNs and LSTMs, and develop practical solutions for real-world challenges.

• Coursera
• 5 hours 22 minutes
• Self-Paced
• Paid Course

Packt

A Practical Approach to Timeseries Forecasting Using Python

Master practical time series forecasting with Python through hands-on projects including COVID-19 prediction, stock forecasting, and birth rate analysis using ARIMA, LSTM, and RNN models.

• Coursera
• 15 hours 33 minutes
• Self-Paced
• Paid Course

Packt

Natural Language Processing - Deep Learning Models in Python

Master deep learning models for NLP with Python, implementing neural networks, CNNs, and RNNs for text classification, embeddings, and sequential data processing using TensorFlow.

• Coursera
• 10 hours 33 minutes
• Self-Paced
• Paid Course

Universidad de Almería

Creative AI: Text and Transformations

Explore how AI transforms writing through generative models, examining bias, ethics, and creative applications while experimenting with text generation tools.

• Coursera
• 13 hours 24 minutes
• Self-Paced
• Paid Course

Learning Deep Learning: Unit 2

Master advanced deep learning with CNNs, RNNs, and Transformers for image classification, NLP, and machine translation using TensorFlow and PyTorch.

• Coursera
• 7 hours 40 minutes
• Self-Paced
• Paid Course

Packt

Deep Learning - Recurrent Neural Networks with TensorFlow

Master recurrent neural networks for time series prediction and NLP tasks using TensorFlow. Implement advanced architectures like GRUs and LSTMs for stock forecasting, image classification, and text analysis.

• Coursera
• 5 hours 41 minutes
• Self-Paced
• Paid Course

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

Packt

Sequence Modeling, Transformers, and Transfer Learning

Master sequence modeling, transformers, and transfer learning to build powerful NLP models using RNNs, attention mechanisms, and fine-tuning techniques for real-world applications.

• Coursera
• 9 hours 48 minutes
• Self-Paced
• Paid Course

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

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

LearnKartS

Become AI-Ready: Deep Learning Fundamentals

Discover how deep learning powers modern AI systems like ChatGPT through hands-on neural network training, backpropagation, and sequence modeling with RNNs and LSTMs.

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

EDUCBA

Sentiment Analysis with RNNs in Keras

Master sentiment analysis using LSTM networks in Keras through hands-on implementation with the IMDB dataset, from preprocessing to model evaluation and prediction.

• Coursera
• 2 hours 41 minutes
• Self-Paced
• Paid Course

Applied Time Series Analysis in Python

822 ratings at Udemy

Use Python and Tensorflow to apply the latest statistical and deep learning techniques for time series analysis

• Udemy
• 6 hours 56 minutes
• Self-Paced
• Paid Course

Nicholas Renotte

Complete Machine Learning and Data Science Courses

Master comprehensive machine learning and data science through hands-on projects including reinforcement learning, object detection, sign language recognition, and data apps.

• YouTube
• 1 day 5 hours 51 minutes
• Self-Paced
• Free Video

CodeEmporium

Deep Learning 201 - Mathematical Foundations

Dive into neural networks' mathematical foundations covering activation functions, optimizers, CNNs, RNNs, LSTMs, GANs, and VAEs with practical explanations.

• YouTube
• 2 hours 19 minutes
• Self-Paced
• Free Video