Overview
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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.
Syllabus
- Course 1: Programming Generative AI: Unit 1
- Course 2: Programming Generative AI: Unit 2
- Course 3: Programming Generative AI: Unit 3
Courses
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Unlock the transformative power of generative AI with our comprehensive online course, designed for learners eager to master the fundamentals and practical applications of deep generative modeling. Begin your journey by demystifying what generative AI truly is, exploring the diverse landscape of multimodal models, and understanding how algorithms can create rich media content from scratch. Delve into the theoretical underpinnings and formalizations that drive deep generative models, gaining insight into the trade-offs between different architectures. Transition seamlessly from theory to practice as you are introduced to the PyTorch framework—one of the most powerful tools in modern deep learning. Through hands-on programming exercises, you’ll learn to manipulate tensors, leverage automatic differentiation, and harness GPU acceleration to build and train your own neural networks. By the end of this course, you’ll not only grasp the core concepts behind generative AI but also acquire the practical skills needed to implement and experiment with deep learning models using industry-standard tools. Whether you’re aspiring to innovate in AI research or apply these skills in real-world projects, this course is your gateway to the future of artificial intelligence.
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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.
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Unlock the full potential of generative AI with our advanced course module focused on state-of-the-art multimodal models. This course is designed for learners eager to bridge the gap between images and text, and to master the latest techniques in AI-driven content generation. You’ll begin by exploring the foundational concepts behind multimodal models, learning how contrastive language-image pre-training enables seamless integration of visual and textual data. Discover how these models power innovative applications like semantic image search, allowing you to query image content without manual labeling. Dive deeper into the mechanics of latent diffusion models and unravel the inner workings of stable diffusion, gaining the skills to transform text prompts into entirely new, never-before-seen images. The course also covers essential strategies for evaluating generative models and introduces efficient methods for fine-tuning and adapting pre-trained models to new styles and subjects. By the end, you’ll be equipped to build, adapt, and optimize cutting-edge text-to-image systems—ready to innovate in creative, research, or commercial settings.
Taught by
Jonathan Dinu and Pearson