Step confidently into the world of generative AI with our expertly crafted online course, designed to equip you with both foundational knowledge and hands-on experience in cutting-edge deep learning techniques. This course guides you through the essential concepts of how computers interpret and generate images and text, starting with the basics of image representation and progressing through advanced architectures like convolutional neural networks and autoencoders. You’ll explore the power of variational autoencoders and diffusion models, learning how these state-of-the-art tools drive modern image generation and enhancement. With practical exercises using industry-standard libraries such as PyTorch and Hugging Face, you’ll gain direct experience building and deploying generative models for both images and text. The course culminates with an in-depth look at natural language processing pipelines and transformer architectures, empowering you to harness large language models for real-world applications. By the end, you’ll have developed a robust skill set in generative AI, ready to innovate in research, creative industries, or technology-driven businesses. Join us and unlock your potential in the rapidly evolving field of artificial intelligence.

Programming Generative AI: Unit 2
本课程是 Programming Generative AI 专项课程 的一部分


位教师:Pearson
访问权限由 New York State Department of Labor 提供
您将学到什么
Understand and implement core generative AI models for images and text, including autoencoders, diffusion models, and transformers.
Gain practical experience with leading deep learning frameworks such as PyTorch and Hugging Face libraries.
Learn to represent, generate, and manipulate images and text using state-of-the-art neural network architectures.
Apply advanced generative techniques for tasks like image enhancement, translation, and natural language inference.
您将获得的技能
要了解的详细信息

添加到您的领英档案
3 项作业
August 2025
了解顶级公司的员工如何掌握热门技能

积累特定领域的专业知识
- 向行业专家学习新概念
- 获得对主题或工具的基础理解
- 通过实践项目培养工作相关技能
- 获得可共享的职业证书

该课程共有1个模块
This module explores how generative models process and create images and text. Learners will understand image representation, convolutional neural networks, and autoencoders, progressing to variational autoencoders for probabilistic image generation. The module introduces diffusion models and practical image generation using Hugging Face’s diffusers library, including advanced tasks like interpolation and restoration. Shifting to text, it covers natural language processing pipelines, word embeddings, and the transformer architecture, culminating in hands-on experience with large language models using the Hugging Face Transformers library. By the end, students gain both theoretical knowledge and practical skills in multimodal generative AI.
涵盖的内容
44个视频3个作业
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。
人们为什么选择 Coursera 来帮助自己实现职业发展

Felipe M.

Jennifer J.

Larry W.







