What is a recurrent neural network?

A recurrent neural network is a type of computer network that follows a sequence of logic to reach a conclusion. It's designed to mimic the thought process of the human brain. Recurrent neural networks can be used to classify data to build sequences, time series, and predictions. They're a component of artificial intelligence and machine learning.

Why is it important to learn about recurrent neural networks?

It's important to learn about recurrent neural networks since they have many uses in computer programming. In particular, you can use deep learning and artificial intelligence to produce predictive results used to solve scientific and business problems ranging from identifying new drug compounds to building sales forecasts. You can utilize recurrent neural networks to identify emotions in tweets, analyze business data, or develop statistics. Recurrent neural networks can help you to manage data problems such as natural language processing, correcting data errors, handling missing entries, and extracting information from small data sets. The technology has a great deal of power, so people who know how to use it properly are in demand.

How can online courses on Coursera help me learn about recurrent neural networks?

Online courses on Coursera can help you learn about recurrent neural networks in several languages and for many different uses. Classes cover TensorFlow, Keras, and natural language processing. Some emphasize theories. Others look at recurrent neural networks as part of other computer science disciplines like artificial intelligence or deep learning. Courses are offered at beginner, intermediate, and advanced levels. Most courses have projects to apply what you learn. Some lead to Professional Certificates and Specializations. Guided Projects are offered to help you demonstrate your current level of understanding.

What skills or experience do I need to already have, before starting to learn about recurrent neural networks?

Before starting to learn about recurrent neural networks, it is helpful to have a basic understanding of computers and programming. Even at a beginner level, some courses assume that you understand the basics of Python. Some courses offer a general introduction to artificial intelligence and machine learning, including the concepts of recurrent neural networks, and do not call for programming or computing skills.

What are the benefits of taking an online Recurrent Neural Network course?

Online Recurrent Neural Network courses offer a convenient and flexible way to enhance your knowledge or learn new Recurrent Neural Network skills. Choose from a wide range of Recurrent Neural Network courses offered by top universities and industry leaders tailored to various skill levels.

What Recurrent Neural Network courses are best for training and upskilling employees or the workforce?

When looking to enhance your workforce's skills in Recurrent Neural Network, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here .

Top Recurrent Neural Network Courses - Learn Recurrent Neural Network Online

Explore the Recurrent Neural Network Course Catalog

Status: Free Trial
DeepLearning.AI
Deep Learning
Skills you'll gain: Computer Vision, Deep Learning, Image Analysis, Natural Language Processing, Artificial Neural Networks, Tensorflow, Generative AI, Supervised Learning, Large Language Modeling, Artificial Intelligence and Machine Learning (AI/ML), Keras (Neural Network Library), Artificial Intelligence, Applied Machine Learning, PyTorch (Machine Learning Library), Machine Learning, MLOps (Machine Learning Operations), Debugging, Performance Tuning, Python Programming, Data-Driven Decision-Making
Build toward a degree
4.8
Rating, 4.8 out of 5 stars
146K reviews
Intermediate · Specialization · 3 - 6 Months
Status: Free Trial
DeepLearning.AI
Sequence Models
Skills you'll gain: Natural Language Processing, Generative AI, Artificial Neural Networks, Tensorflow, Large Language Modeling, Artificial Intelligence and Machine Learning (AI/ML), PyTorch (Machine Learning Library), Deep Learning, Supervised Learning
4.8
Rating, 4.8 out of 5 stars
31K reviews
Intermediate · Course · 1 - 4 Weeks
Status: New
Status: Free Trial
Pearson
Learning Deep Learning: Unit 1
Skills you'll gain: Deep Learning, PyTorch (Machine Learning Library), Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Large Language Modeling, Machine Learning, Python Programming, Algorithms, Network Architecture, Data Processing
Intermediate · Course · 1 - 4 Weeks
Status: Free Trial
DeepLearning.AI
Natural Language Processing
Skills you'll gain: Natural Language Processing, Supervised Learning, Markov Model, Text Mining, Dimensionality Reduction, Artificial Neural Networks, PyTorch (Machine Learning Library), Deep Learning, Tensorflow, Machine Learning Methods, Data Processing, Feature Engineering, Machine Learning Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Algorithms, Keras (Neural Network Library), Unstructured Data, Probability & Statistics, Linear Algebra
4.6
Rating, 4.6 out of 5 stars
6.1K reviews
Intermediate · Specialization · 3 - 6 Months
Status: Free Trial
DeepLearning.AI
Sequences, Time Series and Prediction
Skills you'll gain: Tensorflow, Time Series Analysis and Forecasting, Keras (Neural Network Library), Deep Learning, Predictive Modeling, Artificial Neural Networks, Machine Learning Methods, Forecasting, Data Processing, Machine Learning
4.7
Rating, 4.7 out of 5 stars
5.1K reviews
Intermediate · Course · 1 - 4 Weeks
Status: Preview
Sungkyunkwan University
Fundamentals of CNNs and RNNs
Skills you'll gain: Image Analysis, Computer Vision, Artificial Neural Networks, Natural Language Processing, Deep Learning, Network Architecture, Network Model, Machine Learning
4.4
Rating, 4.4 out of 5 stars
38 reviews
Beginner · Course · 1 - 3 Months

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Coursera Project Network
Deep Learning with PyTorch : Generative Adversarial Network
Skills you'll gain: PyTorch (Machine Learning Library), Generative Model Architectures, Deep Learning, Image Analysis, Python Programming
4.5
Rating, 4.5 out of 5 stars
93 reviews
Intermediate · Guided Project · Less Than 2 Hours
Status: New
Status: Free Trial
Pearson
Learning Deep Learning
Skills you'll gain: Large Language Modeling, Deep Learning, Prompt Engineering, Image Analysis, PyTorch (Machine Learning Library), Tensorflow, LLM Application, Computer Vision, Responsible AI, Natural Language Processing, Generative AI, Artificial Neural Networks, Data Ethics, Multimodal Prompts, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Machine Learning Methods, Artificial Intelligence, Application Deployment, Time Series Analysis and Forecasting
Intermediate · Specialization · 1 - 4 Weeks
Status: Free Trial
Packt
Deep Learning: Recurrent Neural Networks with Python
Skills you'll gain: PyTorch (Machine Learning Library), Tensorflow, Artificial Intelligence, Applied Machine Learning, Artificial Neural Networks, Deep Learning, Application Deployment, Text Mining, Machine Learning, Natural Language Processing, Predictive Modeling, Python Programming, Time Series Analysis and Forecasting, Artificial Intelligence and Machine Learning (AI/ML), Network Architecture, Performance Tuning, Data Science, Data Processing, Data Analysis
Beginner · Specialization · 1 - 3 Months
Status: Free Trial
Johns Hopkins University
Foundations of Neural Networks
Skills you'll gain: Responsible AI, Data Ethics, Artificial Neural Networks, Deep Learning, Machine Learning Algorithms, Reinforcement Learning, Generative AI, Debugging, Artificial Intelligence, Unsupervised Learning, Machine Learning, Computer Vision, Image Analysis, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Applied Machine Learning, Bayesian Statistics, Network Architecture, Linear Algebra, Markov Model
Intermediate · Specialization · 3 - 6 Months
Status: New
Status: Free Trial
Pearson
Learning Deep Learning: Unit 2
Skills you'll gain: PyTorch (Machine Learning Library), Tensorflow, Natural Language Processing, Image Analysis, Deep Learning, Computer Vision, Artificial Neural Networks, Machine Learning Methods, Time Series Analysis and Forecasting, Forecasting, Network Architecture
Intermediate · Course · 1 - 4 Weeks
Status: New
Status: Free Trial
Edureka
Mastering NLP: Tokenization, Sentiment Analysis & Neural MT
Skills you'll gain: Natural Language Processing, Large Language Modeling, Data Ethics, Responsible AI, Text Mining, PyTorch (Machine Learning Library), Artificial Neural Networks, Tensorflow, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Data Processing, Artificial Intelligence, Scikit Learn (Machine Learning Library), Time Series Analysis and Forecasting, Machine Learning, Data Analysis, Unstructured Data, Data Cleansing, Applied Machine Learning, Unified Modeling Language
Intermediate · Specialization · 3 - 6 Months