What skills or experience do I need to already have, before starting to learn Keras?

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.

How do I know if learning Keras is right for me?

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.

What topics can I study that are related to Keras?

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.

What types of places hire people with a background in Keras?

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.

What is Keras and why is it important to learn about?

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.

What kinds of careers can I have with skills in using Keras?

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 .

Can I learn how to use Keras by taking online courses on Coursera?

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.

What are the benefits of taking an online Keras course?

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.

What Keras courses are best for training and upskilling employees or the workforce?

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 .

Top Keras Courses - Learn Keras Online

Imperial College London

Customising your models with TensorFlow 2

Skills you'll gain: Tensorflow, Data Pipelines, Keras (Neural Network Library), Deep Learning, Natural Language Processing, Data Processing, Artificial Neural Networks, Machine Learning Methods, Python Programming, Time Series Analysis and Forecasting

Packt

Building and Training Neural Networks with PyTorch

Skills you'll gain: PyTorch (Machine Learning Library), Artificial Neural Networks, Image Analysis, Deep Learning, Computer Vision, Classification And Regression Tree (CART), Predictive Modeling, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Supervised Learning, Machine Learning, Data Processing, Algorithms

Status: Free

University of London

Foundations of Data Science: K-Means Clustering in Python

Skills you'll gain: Matplotlib, Probability & Statistics, Data Visualization Software, Data Science, Unsupervised Learning, Statistics, NumPy, Python Programming, Pandas (Python Package), Machine Learning Algorithms, Data Analysis, Descriptive Statistics, Data Manipulation

Edureka

Generative AI Applications and Popular Tools

Skills you'll gain: Generative AI, Computer Vision, Image Analysis, OpenAI, Software Development Tools, GitHub, Artificial Intelligence, Application Development, Natural Language Processing, Creative Design

Packt

Deep Learning with Real-World Projects

Skills you'll gain: Matplotlib, Deep Learning, Linear Algebra, Artificial Neural Networks, NumPy, Image Analysis, Keras (Neural Network Library), Data Visualization Software, Machine Learning Algorithms, Seaborn, Pandas (Python Package), Tensorflow, Machine Learning, Applied Machine Learning, Computer Vision, Supervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Data Analysis, PyTorch (Machine Learning Library), Python Programming

Imperial College London

Probabilistic Deep Learning with TensorFlow 2

Skills you'll gain: Generative AI, Tensorflow, Deep Learning, Image Analysis, Bayesian Statistics, Artificial Neural Networks, Machine Learning, Unsupervised Learning, Probability & Statistics, Dimensionality Reduction

Packt

Foundations of Deep Learning and Neural Networks

Skills you'll gain: Deep Learning, Artificial Neural Networks, Image Analysis, Keras (Neural Network Library), Tensorflow, Computer Vision, Artificial Intelligence and Machine Learning (AI/ML), Network Architecture, Network Model, Machine Learning Algorithms, Linear Algebra

Universidad de los Andes

Introducción al deep learning contemporáneo

Skills you'll gain: Generative AI, Deep Learning, Image Analysis, Artificial Neural Networks, Computer Vision, Artificial Intelligence, Network Architecture, Natural Language Processing, Machine Learning, Time Series Analysis and Forecasting

University of Colorado Boulder

Introduction to Deep Learning

Skills you'll gain: Deep Learning, Unsupervised Learning, Keras (Neural Network Library), Computer Vision, Image Analysis, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Machine Learning Methods, Generative AI, Applied Machine Learning, Natural Language Processing, Python Programming

Coursera Project Network

Interpretable machine learning applications: Part 3

Skills you'll gain: Artificial Neural Networks, Tensorflow, Keras (Neural Network Library), Data-Driven Decision-Making, Applied Machine Learning, Classification And Regression Tree (CART), Business Analytics, Predictive Modeling, Deep Learning, Machine Learning, Mortgage Loans

Google Cloud

Intro to TensorFlow 日本語版

Skills you'll gain: Tensorflow, Keras (Neural Network Library), Feature Engineering, Google Cloud Platform, Data Pipelines, Jupyter, Applied Machine Learning, Deep Learning, Machine Learning, Data Import/Export, Scalability

Coursera Project Network

Curso Completo de Deep Learning

Skills you'll gain: Keras (Neural Network Library), Deep Learning, Applied Machine Learning, Artificial Neural Networks, Machine Learning, Data Processing

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Keras Courses Online

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Explore the Keras Course Catalog

Customising your models with TensorFlow 2

Building and Training Neural Networks with PyTorch

Foundations of Data Science: K-Means Clustering in Python

Generative AI Applications and Popular Tools

Deep Learning with Real-World Projects

Probabilistic Deep Learning with TensorFlow 2

Foundations of Deep Learning and Neural Networks

Introducción al deep learning contemporáneo

Introduction to Deep Learning

Interpretable machine learning applications: Part 3

Intro to TensorFlow 日本語版

Curso Completo de Deep Learning

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In summary, here are 10 of our most popular keras courses

Frequently Asked Questions about Keras

What skills or experience do I need to already have, before starting to learn Keras?‎

How do I know if learning Keras is right for me?‎

What topics can I study that are related to Keras?‎

What types of places hire people with a background in Keras?‎

What is Keras and why is it important to learn about?‎

What kinds of careers can I have with skills in using Keras?‎

Can I learn how to use Keras by taking online courses on Coursera?‎

What are the benefits of taking an online Keras course?‎

What Keras courses are best for training and upskilling employees or the workforce?‎

Other topics to explore