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Keras Fundamentals

Updated 03/2026
Take your machine learning skills to the next level. Use the Keras library to create and optimize neural networks to model complex data types.
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PythonArtificial Intelligence16 hr4,157

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Track Description

Keras Fundamentals

In this track, you'll expand your deep learning knowledge and take your machine learning skills to the next level. Working with Keras, you’ll learn about neural networks, the deep learning model workflows, and how to optimize your models. Throughout the track, you'll use deep learning techniques to solve real-world challenges, such as predicting housing prices, and building neural networks to model images and text. By the end of the track, you'll be ready to use Keras to train and test complex, multi-output networks and dive deeper into deep learning.

Prerequisites

There are no prerequisites for this track

  • Course

    4

    Introduction to Deep Learning with Keras

    Learn to start developing deep learning models with Keras.

  • Course

    6

    Image Modeling with Keras

    Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.

  • Project

    bonus

    Building an E-Commerce Clothing Classifier Model with Keras

    Automate e-commerce processes with image classification.

Keras Fundamentals
4 Courses
Track
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FAQs

Is this Track suitable for beginners?

Yes, this track is suitable for beginners. It provides an introduction to Deep Learning using Python and covers the fundamentals of neural networks, deep learning model workflows, and how to optimize your models. It also introduces TensorFlow to help develop linear regression models and neural networks.

What is the programming language of this Track?

The programming language used for this track is Python

Which jobs will benefit from this Track?

This track is beneficial for anyone interested in enhancing their understanding of machine learning techniques such as predictive modelling, supervised learning, and deep learning. It is especially useful for software engineers, data scientists, researchers, and developers.

How will this Track prepare me for my career?

This track equips users with the skills and knowledge to build and deploy deep learning models and to apply them to real-world challenges. By the end of the track, users will be able to use Keras to train and test complex, multi-output networks, and dive deeper into deep learning.

How long does it take to complete this Track?

This track usually takes 16 hours to complete as it consists of several courses that significantly upskill users.

What's the difference between a skill track and a career track?

Skill tracks focus on developing and enhancing particular skills, such as deep learning, whereas career tracks are designed to advance users' career prospects by introducing them to a comprehensive suite of industry-relevant skills.

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