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    • Keras

    Keras Courses Online

    Explore Keras for deep learning model development. Learn to build and train neural networks using this high-level API for TensorFlow.

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    Explore the Keras Course Catalog

    • Status: Free
      Free
      C

      Coursera Project Network

      Deep Learning with PyTorch : Generative Adversarial Network

      Skills you'll gain: Generative AI, PyTorch (Machine Learning Library), Deep Learning, Artificial Neural Networks, Computer Vision, Applied Machine Learning

      4.5
      Rating, 4.5 out of 5 stars
      ·
      88 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • G

      Google Cloud

      Identify Horses or Humans with TensorFlow and Vertex AI

      Skills you'll gain: Tensorflow, Image Analysis, Google Cloud Platform, Computer Vision, Deep Learning, Applied Machine Learning, Data Collection, Visualization (Computer Graphics)

      Beginner · Project · Less Than 2 Hours

    • Status: Free
      Free
      C

      Coursera Project Network

      Deep Learning with PyTorch : Siamese Network

      Skills you'll gain: PyTorch (Machine Learning Library), Artificial Neural Networks, Image Analysis, Deep Learning, Computer Vision

      4.7
      Rating, 4.7 out of 5 stars
      ·
      46 reviews

      Advanced · Guided Project · Less Than 2 Hours

    • C

      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, Financial Forecasting, Business Analytics, Predictive Modeling, Deep Learning, Machine Learning, Commercial Lending, Decision Making, Mortgage Loans, Exploratory Data Analysis, Consumer Lending

      4.5
      Rating, 4.5 out of 5 stars
      ·
      20 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • C

      Coursera Project Network

      ChatGPT for Beginners: SciFi Writing with Dall-e

      Skills you'll gain: Prompt Engineering, ChatGPT, OpenAI, Generative AI, Artificial Intelligence, Storytelling, Storyboarding, Writing, Ideation, Creativity, Editing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      408 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • C

      Coursera Project Network

      Data Analysis with OpenAI API: Save time with GenAI

      Skills you'll gain: Prompt Engineering, Generative AI, Exploratory Data Analysis, OpenAI, Data Analysis, Data-Driven Decision-Making, Trend Analysis, Product Knowledge, Sales Strategy, Application Programming Interface (API), E-Commerce, Data Manipulation, Python Programming

      Intermediate · Guided Project · Less Than 2 Hours

    • Status: Free
      Free
      C

      Coursera Project Network

      Optimize TensorFlow Models For Deployment with TensorRT

      Skills you'll gain: Keras (Neural Network Library), Tensorflow, Deep Learning, Performance Tuning, Machine Learning Methods

      4.5
      Rating, 4.5 out of 5 stars
      ·
      75 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • Status: Free
      Free
      C

      Coursera Project Network

      Transfer Learning for NLP with TensorFlow Hub

      Skills you'll gain: Tensorflow, Natural Language Processing, Keras (Neural Network Library), Text Mining, Deep Learning

      4.8
      Rating, 4.8 out of 5 stars
      ·
      178 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • C

      Coursera Project Network

      GenAI for Data Analysis : OpenAI Assistant API

      Skills you'll gain: Prompt Engineering, Data Analysis, Generative AI, OpenAI, Data Storytelling, Data Visualization Software, Exploratory Data Analysis, Data Manipulation, Artificial Intelligence, Python Programming

      Intermediate · Guided Project · Less Than 2 Hours

    • C

      Coursera Project Network

      Curso Completo de Deep Learning

      Skills you'll gain: Keras (Neural Network Library), Deep Learning, Applied Machine Learning, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Feature Engineering, Machine Learning, Machine Learning Algorithms, Data Processing

      Intermediate · Guided Project · Less Than 2 Hours

    • Status: Free
      Free
      C

      Coursera Project Network

      Deep Learning with PyTorch : GradCAM

      Skills you'll gain: PyTorch (Machine Learning Library), Heat Maps, Image Analysis, Deep Learning, Artificial Neural Networks, Computer Vision

      4.7
      Rating, 4.7 out of 5 stars
      ·
      18 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • C

      Coursera Project Network

      Machine Learning with ChatGPT: Image Classification Model

      Skills you'll gain: ChatGPT, Keras (Neural Network Library), Applied Machine Learning, Image Analysis, Machine Learning Methods, Data Import/Export, Test Data, Performance Tuning, Artificial Neural Networks, Data Processing, Deep Learning

      4.4
      Rating, 4.4 out of 5 stars
      ·
      31 reviews

      Intermediate · Guided Project · Less Than 2 Hours

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

    • Deep Learning with PyTorch : Generative Adversarial Network: Coursera Project Network
    • Identify Horses or Humans with TensorFlow and Vertex AI: Google Cloud
    • Deep Learning with PyTorch : Siamese Network: Coursera Project Network
    • Interpretable machine learning applications: Part 3: Coursera Project Network
    • ChatGPT for Beginners: SciFi Writing with Dall-e: Coursera Project Network
    • Data Analysis with OpenAI API: Save time with GenAI: Coursera Project Network
    • Optimize TensorFlow Models For Deployment with TensorRT: Coursera Project Network
    • Transfer Learning for NLP with TensorFlow Hub: Coursera Project Network
    • GenAI for Data Analysis : OpenAI Assistant API : Coursera Project Network
    • Curso Completo de Deep Learning: Coursera Project Network

    Frequently Asked Questions about 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.‎

    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.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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