Unlock the creative power of generative AI by learning to build your own multimodal systems from the ground up. In this hands-on course, you’ll master deep generative modeling with PyTorch and the Hugging Face ecosystem, progressing from foundational concepts to advanced applications like text-to-image generation and model personalization. Guided by expert instructor Jonathan Dinu, you’ll gain practical skills in manipulating data, training neural networks, and fine-tuning large pre-trained models—empowering you to design innovative AI systems that understand and generate both text and images.
Programming Generative AI Specialization
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Programming Generative AI Specialization
Deep Generative AI Neural Network Multimodal Model. A journey through deep generative modeling—build, train, and personalize AI models using PyTorch.
Instructor: Pearson
Included with 
Get in-depth knowledge of a subject
Intermediate level
Recommended experience
1 month at 5 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject
Intermediate level
Recommended experience
1 month at 5 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
What you'll learn
Develop and implement deep generative models for images and text using PyTorch and Hugging Face libraries.
Build and personalize state-of-the-art multimodal systems, including text-to-image generators like stable diffusion.
Apply advanced techniques for data manipulation, model evaluation, and efficient fine-tuning of large pre-trained AI models.
Overview
Skills you'll gain
Tools you'll learn
What’s included
Shareable certificate
Add to your LinkedIn profile
Taught in English
Recently updated!
August 2025
8 practice exercises
Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from Pearson
Specialization - 3 course series
What you'll learn
Develop a foundational understanding of generative AI and deep generative modeling concepts.
Explore and compare various multimodal generative models and their input/output modalities.
Gain hands-on experience programming with tensors and building neural networks using PyTorch.
Understand the theoretical trade-offs between different generative model architectures and their practical implications.
Skills you'll gain
Category: PyTorch (Machine Learning Library)
Category: Generative AI
Category: Deep Learning
Category: Computer Programming Tools
Category: Large Language Modeling
Category: Artificial Neural Networks
Category: Data Manipulation
Category: Artificial Intelligence and Machine Learning (AI/ML)
What you'll learn
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.
Skills you'll gain
Category: Generative AI
Category: Natural Language Processing
Category: Large Language Modeling
Category: Deep Learning
Category: Unsupervised Learning
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: PyTorch (Machine Learning Library)
Category: Text Mining
Category: Artificial Neural Networks
Category: Image Analysis
Category: Computer Vision
What you'll learn
Understand and implement multimodal models that integrate images and text for advanced AI applications.
Build and optimize semantic image search engines using contrastive language-image pre-training.
Master the principles and practicalities of latent diffusion and stable diffusion for text-to-image generation.
Adapt, fine-tune, and efficiently evaluate pre-trained generative models for new tasks, styles, and real-time performance.
Skills you'll gain
Category: Generative AI
Category: Large Language Modeling
Category: Image Analysis
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Computer Vision
Category: Performance Tuning
Category: Natural Language Processing
Category: Prompt Engineering
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Frequently asked questions
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.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
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.
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