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  • Keras

Keras Courses

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.


Popular Keras Courses and Certifications


  • Status: Free Trial
    Free Trial
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    IBM

    Introduction to Deep Learning & Neural Networks with Keras

    Skills you'll gain: Keras (Neural Network Library), Deep Learning, Transfer Learning, Artificial Neural Networks, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Machine Learning Methods, Image Analysis, Autoencoders, Classification And Regression Tree (CART), Regression Analysis, Network Architecture, Natural Language Processing, Machine Learning, Model Evaluation

    4.7
    Rating, 4.7 out of 5 stars
    ·
    2.1K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    Status: AI skills
    AI skills
    I

    IBM

    IBM Deep Learning with PyTorch, Keras and Tensorflow

    Skills you'll gain: Transfer Learning, PyTorch (Machine Learning Library), Model Evaluation, Vision Transformer (ViT), Keras (Neural Network Library), Deep Learning, Reinforcement Learning, Convolutional Neural Networks, Unsupervised Learning, Autoencoders, Artificial Neural Networks, Recurrent Neural Networks (RNNs), Machine Learning Methods, Generative AI, Generative Adversarial Networks (GANs), Logistic Regression, Tensorflow, Artificial Intelligence and Machine Learning (AI/ML), Image Analysis, Data Preprocessing

    4.5
    Rating, 4.5 out of 5 stars
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    4.1K reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
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    Packt

    Keras Deep Learning & Generative Adversarial Networks (GAN)

    Skills you'll gain: Generative Adversarial Networks (GANs), Exploratory Data Analysis, Model Deployment, Keras (Neural Network Library), NumPy, Transfer Learning, PyTorch (Machine Learning Library), Predictive Modeling, Matplotlib, Data Analysis, Artificial Intelligence, Data Preprocessing, Development Environment, Pandas (Python Package), Deep Learning, Classification And Regression Tree (CART), Artificial Neural Networks, Image Analysis, Machine Learning, Data Science

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
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    IBM

    Deep Learning with Keras and Tensorflow

    Skills you'll gain: Keras (Neural Network Library), Reinforcement Learning, Convolutional Neural Networks, Unsupervised Learning, Deep Learning, Autoencoders, Tensorflow, Recurrent Neural Networks (RNNs), Machine Learning Methods, Generative AI, Generative Adversarial Networks (GANs), Transfer Learning, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Computer Vision, Model Evaluation, Performance Tuning

    4.4
    Rating, 4.4 out of 5 stars
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    1K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
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    EDUCBA

    Keras Deep Learning Projects with TensorFlow

    Skills you'll gain: Embeddings, Natural Language Processing, Keras (Neural Network Library), Generative AI, Convolutional Neural Networks, Transfer Learning, Recurrent Neural Networks (RNNs), Model Evaluation, Image Analysis, Artificial Neural Networks, Text Mining, Computer Vision, Data Preprocessing, Tensorflow, Deep Learning, Model Deployment, Applied Machine Learning, Google Cloud Platform, Jupyter, Matplotlib

    Beginner · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    IBM AI Engineering

    Skills you'll gain: Prompt Engineering, Apache Spark, Large Language Modeling, Transfer Learning, PyTorch (Machine Learning Library), Model Evaluation, Computer Vision, Retrieval-Augmented Generation, Unsupervised Learning, Generative Model Architectures, Generative AI, PySpark, Vision Transformer (ViT), Keras (Neural Network Library), LLM Application, Supervised Learning, Vector Databases, Machine Learning, Python Programming, Data Science

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    22K reviews

    Intermediate · Professional Certificate · 3 - 6 Months

What brings you to Coursera today?

  • Status: New
    New
    Status: Free Trial
    Free Trial
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    Packt

    Deep Learning with TensorFlow

    Skills you'll gain: Recurrent Neural Networks (RNNs), Transfer Learning, Tensorflow, Artificial Neural Networks, Embeddings, Keras (Neural Network Library), Deep Learning, Time Series Analysis and Forecasting, Image Analysis, Classification Algorithms, Convolutional Neural Networks, Natural Language Processing, Computer Vision, Forecasting, Supervised Learning, Machine Learning Algorithms, Machine Learning, Predictive Analytics, Model Evaluation, Predictive Modeling

    Intermediate · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    Imperial College London

    TensorFlow 2 for Deep Learning

    Skills you'll gain: Tensorflow, Recurrent Neural Networks (RNNs), Autoencoders, Generative Model Architectures, Data Pipelines, Keras (Neural Network Library), Model Evaluation, Deep Learning, Image Analysis, Transfer Learning, Convolutional Neural Networks, Applied Machine Learning, Bayesian Statistics, Supervised Learning, Natural Language Processing, Computer Vision, Model Deployment, Artificial Neural Networks, Data Preprocessing, Probability Distribution

    4.8
    Rating, 4.8 out of 5 stars
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    720 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    G
    N
    G
    N

    Multiple educators

    Machine Learning for Trading

    Skills you'll gain: Tensorflow, Keras (Neural Network Library), Machine Learning Methods, Model Evaluation, Machine Learning, Google Cloud Platform, Machine Learning Algorithms, Applied Machine Learning, Financial Trading, Reinforcement Learning, Recurrent Neural Networks (RNNs), Supervised Learning, Data Pipelines, Time Series Analysis and Forecasting, Statistical Machine Learning, Technical Analysis, Deep Learning, Securities Trading, Portfolio Management, Artificial Intelligence and Machine Learning (AI/ML)

    3.8
    Rating, 3.8 out of 5 stars
    ·
    1.2K reviews

    Intermediate · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    L

    LearnQuest

    AI for Scientific Research

    Skills you'll gain: Data Preprocessing, Feature Engineering, Model Evaluation, Bioinformatics, Exploratory Data Analysis, Random Forest Algorithm, Pandas (Python Package), Scikit Learn (Machine Learning Library), Applied Machine Learning, Data Manipulation, Dimensionality Reduction, Data Cleansing, Keras (Neural Network Library), Data Transformation, NumPy, Classification Algorithms, Tensorflow, Artificial Neural Networks, Machine Learning, Data Science

    3.2
    Rating, 3.2 out of 5 stars
    ·
    82 reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    P

    Packt

    Deep Learning: Convolutional Neural Networks with TensorFlow

    Skills you'll gain: Transfer Learning, Keras (Neural Network Library), Embeddings, Deep Learning, Image Analysis, Computer Vision, Natural Language Processing, Data Preprocessing

    Intermediate · Course · 1 - 4 Weeks

  • C

    Coursera

    CNNs with TensorFlow: Basics of Machine Learning

    Skills you'll gain: Tensorflow, Convolutional Neural Networks, Keras (Neural Network Library), Matplotlib, Artificial Neural Networks, Image Analysis, Deep Learning, Applied Machine Learning, Python Programming, Model Evaluation, Adaptability, Problem Solving

    Intermediate · Guided Project · Less Than 2 Hours

Searches related to keras

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keras deep learning & generative adversarial networks (gan)
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1234…16

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

  • Introduction to Deep Learning & Neural Networks with Keras: IBM
  • IBM Deep Learning with PyTorch, Keras and Tensorflow: IBM
  • Keras Deep Learning & Generative Adversarial Networks (GAN): Packt
  • Deep Learning with Keras and Tensorflow: IBM
  • Keras Deep Learning Projects with TensorFlow: EDUCBA
  • IBM AI Engineering: IBM
  • Deep Learning with TensorFlow: Packt
  • TensorFlow 2 for Deep Learning: Imperial College London
  • Machine Learning for Trading: Google Cloud
  • AI for Scientific Research: LearnQuest

Frequently Asked Questions about Keras

Keras is an open-source software library that provides a user-friendly interface for building and training deep learning models. It is built on top of TensorFlow and simplifies the process of creating complex neural networks. Keras is important because it allows developers and data scientists to prototype and experiment with deep learning models quickly, making it accessible for those who may not have extensive programming backgrounds. Its simplicity and flexibility have made it a popular choice in both academic and industry settings.‎

With skills in Keras, you can pursue various job roles in the tech industry. Common positions include machine learning engineer, data scientist, AI researcher, and deep learning engineer. These roles often involve developing algorithms and models that can analyze data, make predictions, and improve decision-making processes. As organizations increasingly rely on data-driven insights, the demand for professionals skilled in Keras and deep learning continues to grow.‎

To effectively learn Keras, you should focus on several key skills. First, a solid understanding of Python programming is essential, as Keras is primarily used with this language. Additionally, knowledge of machine learning concepts, neural networks, and data preprocessing techniques will be beneficial. Familiarity with TensorFlow, the underlying framework for Keras, is also important. Finally, hands-on experience with building and training models will help reinforce your learning.‎

Some of the best online courses for learning Keras include the Deep Learning with Keras and Tensorflow course, which provides a comprehensive introduction to deep learning concepts. The Introduction to Deep Learning & Neural Networks with Keras course is also highly recommended for beginners. For those looking to specialize further, the Keras Deep Learning & Generative Adversarial Networks (GAN) Specialization offers an in-depth exploration of advanced topics.‎

Yes. You can start learning keras on Coursera for free in two ways:

  1. Preview the first module of many keras courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in keras, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn Keras effectively, start by familiarizing yourself with Python and the basics of machine learning. Then, explore online courses that focus on Keras, such as those mentioned earlier. Practice by building simple models and gradually increase complexity as you gain confidence. Engaging with community forums and participating in projects can also enhance your learning experience and provide valuable insights.‎

Keras courses typically cover a range of topics, including the fundamentals of neural networks, model architecture, training and evaluation techniques, and practical applications of deep learning. You may also learn about advanced topics such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs). These topics equip you with the knowledge needed to tackle real-world problems using deep learning.‎

For training and upskilling employees or the workforce in Keras, the IBM Deep Learning with PyTorch, Keras and Tensorflow Professional Certificate is an excellent choice. It provides a structured learning path that covers essential concepts and practical skills. Additionally, the Deep Learning with Keras and Practical Applications course offers hands-on experience that can be beneficial for teams looking to implement deep learning solutions.‎

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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