Overview of Course

Keras Training is a comprehensive course designed to help you master deep learning using Keras, a high-level neural networks API written in Python. With this course, you will learn how to build, train, and deploy deep learning models with Keras, and gain the skills needed to tackle real-world machine learning problems.

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Course Highlights

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Learn the fundamentals of deep learning using Keras

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Understand how to build, train, and deploy neural networks

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Use Keras to solve real-world machine learning problems




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    Real-world Projects

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Skills You’ll Learn

#1

Deep learning concepts and techniques

#2

Building and training neural networks

#3

Working with image data

#4

Convolutional and recurrent neural networks

#5

Deploying models to production

#6

Solving real-world machine learning problems

Training Options

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1-on-1 Training

On Request
  • Option Item Access to live online classes
  • Option Item Flexible schedule including weekends
  • Option Item Hands-on exercises with virtual labs
  • Option Item Session recordings and learning courseware included
  • Option Item 24X7 learner support and assistance
  • Option Item Book a free demo before you commit!
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Corporate Training

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  • Option Item Everything in 1-on-1 Training plus
  • Option Item Custom Curriculum
  • Option Item Extended access to virtual labs
  • Option Item Detailed reporting of every candidate
  • Option Item Projects and assessments
  • Option Item Consulting Support
  • Option Item Training aligned to business outcomes
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Course Reviews

Curriculum

  • Introduction to Keras and its history
  • The importance of Keras in deep learning
  • The benefits of using Keras over other deep learning frameworks
  • Key features of Keras

  • Installing Keras on different platforms
  • Configuring Keras for different backends (TensorFlow, Theano, etc.)
  • Keras API and its functionalities
  • Keras layers and models

  • Introduction to Convolutional Neural Networks (ConvNets)
  • Basic architecture of ConvNets
  • Training and evaluation of ConvNets
  • Common applications of ConvNets

  • Introduction to Generative Adversarial Networks (GANs)
  • Understanding the GAN framework and architecture
  • Training and evaluation of GANs
  • Introduction to Wavenet and its applications

  • Introduction to word embeddings
  • Different techniques for word embeddings (Word2Vec, GloVe, etc.)
  • Using pre-trained word embeddings in Keras
  • Evaluating word embeddings

  • Introduction to Recurrent Neural Networks (RNNs)
  • Basic architecture of RNNs
  • Training and evaluation of RNNs
  • Common applications of RNNs

  • Introduction to additional deep learning models (e.g., Autoencoders, Boltzmann Machines, etc.)
  • Understanding the architecture and functionality of these models
  • Training and evaluation of these models
  • Common applications of these models.
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Description

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Target Audience:

  • Beginner to intermediate level learners in deep learning and Keras
  • Machine learning professionals looking to upskill in Keras
  • Developers interested in building and deploying deep learning models using Keras
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Prerequisite:

  • Basic knowledge of Python programming
  • Understanding of machine learning concepts
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Benefits of the course:

  • Hands-on experience with Keras and deep learning techniques
  • Practical projects to work on
  • Flexibility to learn at your own pace
  • Certificate of completion
  • Access to online community for networking and support
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Exam details to pass the course:

  • There is no exam to pass the course.
  • You will receive a certificate of completion upon finishing the course.
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Certification path:

  • To learn this course, you don't need any prior certification.
  • However, upon completing the course, you will receive a certificate of completion from Skillzcafe.
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Career option:

  • Machine Learning Engineer
  • Data Scientist
  • Deep Learning Engineer
  • AI Researcher
  • Computer Vision Engineer

Career option:

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Career option:
  • Bullet Icon Machine Learning Engineer
  • Bullet Icon Data Scientist
  • Bullet Icon Deep Learning Engineer
  • Bullet Icon AI Researcher
  • Bullet Icon Computer Vision Engineer

FAQs

No, this course is designed for both beginners and intermediate level learners.

You will need a computer with a working internet connection and access to Python and Keras libraries. The course provides instructions on how to install the required software.

Yes, you will have lifetime access to the course content, including any updates or revisions made in the future.

Yes, upon completing the course, you will receive a certificate of completion from Skillzcafe.

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