Keras courses can help you learn neural network design, model training, and performance evaluation techniques. You can build skills in optimizing hyperparameters, implementing convolutional and recurrent layers, and using transfer learning for various applications. Many courses introduce tools like TensorFlow and Python, that support developing AI models and deploying them in practical work.

Skills you'll gain: Keras (Neural Network Library), Deep Learning, Artificial Neural Networks, Tensorflow, Machine Learning Methods, Image Analysis, Computer Vision, Regression Analysis, Network Architecture, Network Model, Natural Language Processing, Machine Learning
Intermediate · Course · 1 - 3 Months

Skills you'll gain: PyTorch (Machine Learning Library), Keras (Neural Network Library), Deep Learning, Reinforcement Learning, Unsupervised Learning, Artificial Neural Networks, Machine Learning Methods, Generative AI, Tensorflow, Artificial Intelligence and Machine Learning (AI/ML), Image Analysis, Computer Vision, Statistical Modeling, Artificial Intelligence, Geospatial Information and Technology, Machine Learning, Regression Analysis, Data Pipelines, Network Architecture, Network Model
Intermediate · Professional Certificate · 3 - 6 Months

Skills you'll gain: Natural Language Processing, Keras (Neural Network Library), Generative AI, Generative Model Architectures, Image Analysis, Artificial Neural Networks, Text Mining, Computer Vision, Tensorflow, Deep Learning, Feature Engineering, Performance Testing, Machine Learning Methods, Applied Machine Learning, Google Cloud Platform, Application Development, Data Processing, Systems Development, Python Programming, Data Transformation
Beginner · Specialization · 1 - 3 Months

Skills you'll gain: Prompt Engineering, Apache Spark, Large Language Modeling, PyTorch (Machine Learning Library), Computer Vision, Unsupervised Learning, Generative AI, PySpark, Keras (Neural Network Library), Supervised Learning, Deep Learning, Reinforcement Learning, Regression Analysis, LLM Application, Scikit Learn (Machine Learning Library), Applied Machine Learning, Natural Language Processing, Machine Learning, Python Programming, Data Science
Build toward a degree
Intermediate · Professional Certificate · 3 - 6 Months

Skills you'll gain: Keras (Neural Network Library), Reinforcement Learning, Unsupervised Learning, Deep Learning, Tensorflow, Machine Learning Methods, Generative AI, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Natural Language Processing, Performance Tuning
Intermediate · Course · 1 - 3 Months

Skills you'll gain: Artificial Intelligence and Machine Learning (AI/ML), Exploratory Data Analysis, Generative AI, Keras (Neural Network Library), NumPy, Data Processing, PyTorch (Machine Learning Library), Predictive Modeling, Matplotlib, Data Analysis, Generative Model Architectures, Development Environment, Pandas (Python Package), Image Analysis, Deep Learning, Classification And Regression Tree (CART), Artificial Neural Networks, Artificial Intelligence, Machine Learning, Data Science
Intermediate · Specialization · 3 - 6 Months

Skills you'll gain: Keras (Neural Network Library), Tensorflow, Applied Machine Learning, Deep Learning, Machine Learning, Computer Vision
Intermediate · Guided Project · Less Than 2 Hours

Skills you'll gain: Tensorflow, Artificial Neural Networks, Keras (Neural Network Library), Deep Learning, Time Series Analysis and Forecasting, Image Analysis, Natural Language Processing, Computer Vision, Forecasting, Classification And Regression Tree (CART), Supervised Learning, Machine Learning, Text Mining, Predictive Analytics, NumPy, Network Architecture, Data Processing, Data Science
Intermediate · Specialization · 1 - 3 Months

Imperial College London
Skills you'll gain: Tensorflow, Generative Model Architectures, Data Pipelines, Keras (Neural Network Library), Deep Learning, Image Analysis, Computer Programming, Program Development, Data Validation, Applied Machine Learning, Bayesian Statistics, Supervised Learning, Natural Language Processing, Data Processing, Predictive Modeling, Computer Vision, Machine Learning Methods, Artificial Neural Networks, Machine Learning, Unsupervised Learning
Intermediate · Specialization · 3 - 6 Months

Multiple educators
Skills you'll gain: Tensorflow, Keras (Neural Network Library), Machine Learning, Google Cloud Platform, Machine Learning Algorithms, Applied Machine Learning, Financial Trading, Reinforcement Learning, Supervised Learning, Data Pipelines, Time Series Analysis and Forecasting, Statistical Machine Learning, Technical Analysis, Deep Learning, Securities Trading, Portfolio Management, Market Trend, Artificial Intelligence and Machine Learning (AI/ML), Financial Market, Artificial Neural Networks
Intermediate · Specialization · 1 - 3 Months
DeepLearning.AI
Skills you'll gain: Generative AI, Tensorflow, Computer Vision, Image Analysis, Generative Model Architectures, Deep Learning, Keras (Neural Network Library), Artificial Neural Networks, Distributed Computing, Unsupervised Learning, Network Model, Visualization (Computer Graphics), Performance Tuning, NumPy, Object Oriented Programming (OOP), Heat Maps, Network Architecture
Intermediate · Specialization · 3 - 6 Months

Skills you'll gain: Keras (Neural Network Library), Tensorflow, Image Analysis, Artificial Neural Networks, Deep Learning, Machine Learning Methods, Computer Vision, Machine Learning
Beginner · Guided Project · Less Than 2 Hours
Since Keras is based in Python, you'll need to have experience using this programming language before starting to learn Keras. You should also have a basic understanding of foundational machine learning concepts. It's also helpful to have an understanding of what deep learning is as well as strong math skills.‎
Learning Keras is likely right for you if you're pursuing a career in neural network framework and deep learning. Deep learning refers to methods of machine learning that are based on algorithms created in artificial neural networks that are modeled after the function and structure of the brain. You might be working toward a career or already in one as a software engineer, for example, or a data analyst, data engineer, research analyst, software developer, or bioinformatics analyst. If so, learning Keras may be right for you.‎
TensorFlow, Theano, and CNTK are three topics you can study that are closely related to Keras because Keras runs on top of these libraries. You can also study the human brain to form a deeper understanding of the premise of neural networks. Any topic related to machine learning may also be of interest to you, such as supervised, unsupervised, and reinforcement learning; inductive, deductive, and transductive learning; or multi-task, active, online, transfer, and ensemble learning. You can also learn more about deep learning and neural networks.‎
Places that hire people with a background in Keras include companies and organizations that employ data and software analysts and developers. For example, you'll find people with a background in Keras working for cloud computing platforms like Amazon Web Services, professional services networks like Deloitte, telecommunications companies such as Verizon, and cybersecurity companies like Carbon Black. Other notable employers of people with a background in Keras include JP Morgan Chase Bank, Microsoft, Facebook, Ford Motor Company, and Lockheed Martin.‎
Keras is an API for machine learning applications written in Python and built on top of the open-source TensorFlow platform. It provides an efficient and easy-to-use interface for TensorFlow, which has become one of the most popular software platforms for machine learning due to its flexibility and a comprehensive ecosystem of tools and resources; for instance, the TensorFlow.js library allows you to build machine learning applications to run in web browsers on JavaScript. By allowing researchers and developers to go from their ideas to results as quickly as possible while still harnessing the power of TensorFlow, Keras is an important tool for enabling fast experimentation for machine learning applications.
In addition to providing an approachable interface for TensorFlow, developing applications in Keras offers a number of other advantages. It allows for computation to be scaled to use many devices, harnessing potentially tens of thousands of CPUs and GPUs for advanced applications. It can also export programs to external runtimes such as servers, web browsers, or mobile and embedded devices. This flexibility and power, in addition to ease of use, has made Keras an essential tool for simple machine learning tasks as well as high-level deep learning tasks such as creating artificial neural networks.‎
TensorFlow and Keras are essential, industry-standard tools for developing machine learning, deep learning, and artificial intelligence (AI) applications. These cutting-edge skills are in high demand from technology companies seeking to harness user data to provide new or improved services, as well as companies building next-generation products in the automotive industry, medicine, robotics, and other areas. This high demand translates into high pay; in addition to experiencing the excitement of working on the forefront of technology, AI engineers receive an average annual salary of $114,121 according to Glassdoor.‎
Yes! In fact, Coursera lets you learn about Keras, TensorFlow, and other topics in machine learning and artificial intelligence (AI) in several different ways. You can take courses from top-ranked schools like Imperial College London, or from industry leaders like IBM and deeplearning.ai. Additionally, you can build skills in Keras by completing guided tutorials side-by-side experienced instructors with the Coursera Project Network, providing a more hands-on way to learn. Regardless of what best suits your needs, Coursera lets you learn remotely on a flexible schedule, allowing you to fit this valuable education into your existing studies, work, or family life.‎
Online Keras courses offer a convenient and flexible way to enhance your knowledge or learn new Keras skills. Choose from a wide range of Keras courses offered by top universities and industry leaders tailored to various skill levels.‎
When looking to enhance your workforce's skills in Keras, 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.‎
Deep learning with Keras in Python involves building neural networks using Keras, a high-level API running on top of TensorFlow. It simplifies model design, training, and evaluation for tasks like image recognition and natural language processing. Courses like Deep Learning Specialization by Andrew Ng on Coursera include hands-on projects using Keras and Python.‎