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Deep Learning in Python

Updated 03/2026
Continue your machine learning journey into deep learning. Use the PyTorch library to create neural networks to model different data types.
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Track Description

Deep Learning in Python

Discover deep learning and explore how this branch of machine learning is changing the world. Join the deep learning revolution today!If you’re familiar with traditional machine learning and want to begin your journey into deep learning, this is an ideal place to start. You’ll cover the use cases for deep learning and become familiar with the popular PyTorch framework for building deep learning models in Python.You’ll learn how to build models to solve a variety of real-world problems involving different data types. You’ll predict whether water is drinkable or not, predict electricity consumption from a time series dataset, classify different cloud types from photographs, and identify the language and characters used in handwritten text.You’ll explore advanced architectures and pre-trained models for other image tasks, including object recognition, image segmentation, and image generation.Finally, you’ll learn deep learning techniques for working with text data. You’ll process and encode text for modeling and explore the strengths of different architectures and pre-trained models for text classification and generation. You’ll also begin using one of the most exciting architectures around: the Transformers architecture, which underpins large language models like ChatGPT.By the time you’re finished, you’ll understand essential deep learning concepts and be able to apply them to a variety of different situations in Python.

Prerequisites

There are no prerequisites for this track

  • Course

    1

    Introduction to Deep Learning with PyTorch

    Learn how to build your first neural network, adjust hyperparameters, and tackle classification and regression problems in PyTorch.

  • Project

    bonus

    Building an E-Commerce Clothing Classifier Model

    Automate e-commerce processes with image classification.

  • Course

    5

    Deep Learning for Text with PyTorch

    Discover the exciting world of Deep Learning for Text with PyTorch and unlock new possibilities in natural language processing and text generation.

Deep Learning in Python
5 Courses
Track
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FAQs

Is this Track suitable for beginners?

Yes, this Track is suitable for beginners as it starts with an Introduction to Deep Learning with PyTorch course.

What is the programming language of this Track?

The programming language for this Track is Python.

Which jobs will benefit from this Track?

This Track will benefit those who are interested in data science and deep learning, and those who are looking to upskill in their current job or seek new job opportunities in this field.

How will this Track prepare me for my career?

This Track will provide you with essential deep learning concepts and skills that can be applied to a variety of real-world problems, making you more competitive and attractive in the job market.

How long does it take to complete this Track?

This Track will take approximately 16 hours to complete, as it consists of several courses.

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

A skill track focuses on a specific set of skills, while a career track covers a broader range of topics and skills necessary for a specific career path.

What are the four courses included in this Track?

The four courses included in this Track are Introduction to Deep Learning with PyTorch, Intermediate Deep Learning with PyTorch, Deep Learning for Images with PyTorch, and Deep Learning for Text with PyTorch.

What is the PyTorch framework and why is it important in deep learning?

The PyTorch framework is a popular tool for building deep learning models in Python, making it easier to apply deep learning techniques to solve real-world problems.

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