Can I take the course for free?

No, you cannot take this course for free. When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you cannot afford the fee, you can apply for financial aid.

Will I earn university credit for completing the Specialization?

This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

PyTorch Ultimate 2024 - From Basics to Cutting-Edge 专项课程

PyTorch Ultimate 2024 - From Basics to Cutting-Edge 专项课程

Master Deep Learning with PyTorch. Master deep learning with PyTorch, covering Regression, CNNs, GANs, NLP, and more.

位教师：Packt - Course Instructors

4,220 人已注册

包含在 Coursera Plus 中

了解更多

3 门课程系列

深入学习学科知识

4.6

（50 条评论）

中级等级

推荐体验

4 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

3 门课程系列

深入学习学科知识

4.6

（50 条评论）

中级等级

推荐体验

4 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

您将学到什么

Identify and describe the fundamental concepts of PyTorch, machine learning, and deep learning, including neural networks.
Implement PyTorch models for tasks such as classification and regression, incorporating principles of deep learning.
Evaluate and optimize model performance using metrics and techniques for underfitting, overfitting, and hyperparameter tuning.
Develop advanced AI applications using GANs, CNNs, and RNNs, and deploy models effectively.

要了解的详细信息

可分享的证书

添加到您的领英档案

授课语言：英语（English）

了解顶级公司的员工如何掌握热门技能

了解关于 Coursera for Business 的更多信息

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

精进特定领域的专业知识

向大学和行业专家学习热门技能
借助实践项目精通一门科目或一个工具
培养对关键概念的深入理解
通过 Packt 获得职业证书

专业化 - 3门课程系列

Updated in May 2025.

This course now features Coursera Coach!

A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course.

Embark on a transformative learning experience with our PyTorch Ultimate 2024 course. Begin with a solid foundation, understanding the key topics and objectives, and seamlessly transition through machine learning essentials and deep learning principles. From setting up your environment to mastering tensors and neural networks, each section is meticulously crafted to build your expertise. Advanced modules dive into PyTorch modeling, CNNs, RNNs, GANs, and more, ensuring you stay ahead in the rapidly evolving field of AI. With practical coding exercises and real-world applications, this course is your gateway to becoming a PyTorch expert.

Our course is designed for tech professionals, data scientists, and AI enthusiasts eager to deepen their understanding of PyTorch. Prior experience in Python and basic machine learning concepts is recommended. By the end of the course, you'll be equipped with the skills to tackle complex AI projects and leverage PyTorch for innovative solutions.

应用的学习项目

The included projects offer practical, hands-on experience where learners apply their skills to real-world problems. These projects range from constructing neural networks from scratch to developing complex models for image, audio, and object detection tasks. By engaging with these projects, learners will solve authentic problems, enhancing their ability to deploy robust deep-learning solutions in various practical scenarios.

Foundations and Core Concepts of PyTorch

第 1 门课程8小时

您将学到什么

Set up and configure a PyTorch environment.
Understand fundamental AI and machine learning concepts.
Build, train, and evaluate neural networks from scratch, utilizing various optimization techniques
Apply PyTorch to real-world deep learning tasks.

您将获得的技能

类别：PyTorch (Machine Learning Library)

类别：Artificial Neural Networks

类别：Deep Learning

类别：Regression Analysis

类别：Machine Learning

类别：Software Installation

类别：Development Environment

类别：Performance Tuning

类别：System Configuration

类别：Artificial Intelligence

类别：Supervised Learning

类别：Python Programming

Building and Training Neural Networks with PyTorch

第 2 门课程9小时

您将学到什么

Build and train neural networks using PyTorch for various tasks.
Implement classification models with multi-class, multi-label datasets, and CNNs for image and audio classification.
Apply object detection techniques using the YOLO algorithm.
Explore neural style transfer, transfer learning, and implement RNNs and LSTM networks.

您将获得的技能

类别：PyTorch (Machine Learning Library)

类别：Exploratory Data Analysis

类别：Artificial Neural Networks

类别：Development Environment

类别：Artificial Intelligence and Machine Learning (AI/ML)

类别：Machine Learning Methods

类别：Computer Vision

类别：Data Processing

类别：Supervised Learning

类别：Deep Learning

Advanced PyTorch Techniques and Applications

第 3 门课程14小时

您将学到什么

Create and assess ML models for specific datasets, evaluating performance with proper metrics.
Design autoencoders for dimensionality reduction and build GANs for data simulation, analyzing quality.
Develop Graph Neural Networks for graph data and implement Transformers, including Vision Transformers.
Enhance models with semi-supervised learning using limited data, and deploy them with Flask on Google Cloud.

您将获得的技能

类别：PyTorch (Machine Learning Library)

类别：Application Deployment

类别：Google Cloud Platform

类别：Deep Learning

类别：Flask (Web Framework)

类别：Natural Language Processing

类别：Supervised Learning

类别：Dimensionality Reduction

类别：Computer Vision

类别：Machine Learning

类别：Text Mining

类别：Unsupervised Learning

类别：Generative AI

类别：Network Model

获得职业证书

将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。

位教师

Packt - Course Instructors

Packt

971 门课程229,122 名学生

提供方

Packt

人们为什么选择 Coursera 来帮助自己实现职业发展

Felipe M.

自 2018开始学习的学生

''能够按照自己的速度和节奏学习课程是一次很棒的经历。只要符合自己的时间表和心情，我就可以学习。'

Jennifer J.

自 2020开始学习的学生

''我直接将从课程中学到的概念和技能应用到一个令人兴奋的新工作项目中。'

Larry W.

自 2021开始学习的学生

''如果我的大学不提供我需要的主题课程，Coursera 便是最好的去处之一。'

Chaitanya A.

''学习不仅仅是在工作中做的更好：它远不止于此。Coursera 让我无限制地学习。'

通过 Coursera Plus 开启新生涯

无限制访问 10,000+ 世界一流的课程、实践项目和就业就绪证书课程 - 所有这些都包含在您的订阅中

了解更多

通过在线学位推动您的职业生涯

获取世界一流大学的学位 - 100% 在线

探索学位

加入超过 3400 家选择 Coursera for Business 的全球公司

提升员工的技能，使其在数字经济中脱颖而出

了解更多

常见问题

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.