Opleiding: Image Generation with AI

Image Generation with AI. 

Ontdek hoe kunstmatige intelligentie de wereld van beeldgeneratie transformeert met onze Image Generation with AI Training. Leer de nieuwste AI-technieken voor het creëren van verbluffende beelden. Boek nu en stap in de toekomst van visuele content!

Deze Learning Kit met meer dan 8 leeruren is verdeeld in drie sporen:

Cursusinhoud

Introduction to AI-powered Image Generation

• In this course, examine the pros and cons of generative AI (GenAI), the history of image generation, the uses of AI in creative content generation, and generative AI models and methods. Next, discover how to use generative AI to create content, generative AI pipeline components, and use cases for generative AI. Finally, learn about popular generative AI frameworks and tools, ethical considerations of generative AI, how AI influences art, the implications of generative AI, and the possible future of generative AI.

Image Generation with AI: Image Generation Frameworks

• In this course, you’ll explore image generation frameworks, beginning with variational autoencoders (VAEs), generative adversarial networks (GANs), and comparing GANs and VAEs. Then you’ll explore GAN architectures, GAN use cases, GAN training, and the DCGAN, WGAN, CycleGAN, and StyleGAN architectures. Finally, you’ll learn about autoregressive models, autoregressive models in comparison to other techniques, diffusion models, diffusion model use cases, and the pros and cons of image generation frameworks.

Mathematical Foundations of Image Generation

• In this course, you will explore the mathematical foundations of image generation, beginning with the role of generative adversarial networks (GANs) in image generation, basic GAN usage, probability distributions, and generative models. Then you will learn about noise vectors, activation functions in GANs, and loss functions. Next, you will investigate backpropagation, conditional GANs, and style transfer methods. You will discover latent space and adversarial training. Finally, you will create your own GAN-based image generation project.

Image Generation with AI: Mastering Image Editing with VAEs

In this course, you’ll be introduced to image editing with variational autoencoders (VAEs), beginning with fundamental principles of VAEs, probabilistic encoding and decoding with VAEs, and latent space in generative models. Then you’ll be introduced to Keras, the Keras Environment, image editing with VAEs, and VAE training. Finally, you’ll explore latent space variables in Keras, how to build an autoencoder in Keras, how to generate images with Keras, and Keras case studies.

Image Generation with AI: Image Generation with Stable Diffusion in Keras

• In this course, you will be introduced to image generation with Stable Diffusion in Keras, beginning with an overview of Stable Diffusion and diffusion models. Then you will examine variations of diffusion models and uses for diffusion models. You will explore high-resolution image creation, realism, and detail enhancement with Stable Diffusion. Next, you will learn how to implement Stable Diffusion with Keras. Finally, you will investigate methods for prompt creation, inpainting, latent diffusion, and Stable Diffusion models.

Image Generation with AI: High-resolution Image Generation

• In this course, you will be introduced to high-resolution image generation with AI, beginning with Stable Diffusion use cases, model construction, and model training. Then you will delve into fine-tuning strategies, denoising diffusion models with Keras, and high-resolution image generation in Keras. Next, you will explore the advantages of high-resolution image generation in Keras, the inner workings of image generation, and the impact that Stable Diffusion has on AI-powered image generation. Finally, you will investigate the steps involved in moving an image generator to a cloud provider.

Assessment:

• Final Exam: Image Generation with AI

Specificaties

Taal: Engels
Kwalificaties van de Instructeur: Gecertificeerd
Cursusformaat en Lengte: Lesvideo's met ondertiteling, interactieve elementen en opdrachten en testen
Lesduur: 8:40 uur
Assesments: De assessment test uw kennis en toepassingsvaardigheden van de onderwerpen uit het leertraject. Deze is 365 dagen beschikbaar na activering.
Online Virtuele labs: Ontvang 12 maanden toegang tot virtuele labs die overeenkomen met de traditionele cursusconfiguratie. Actief voor 365 dagen na activering, beschikbaarheid varieert per Training.
Online mentor: U heeft 24/7 toegang tot een online mentor voor al uw specifieke technische vragen over het studieonderwerp. De online mentor is 365 dagen beschikbaar na activering, afhankelijk van de gekozen Learning Kit.
Voortgangsbewaking: Ja
Toegang tot Materiaal: 365 dagen
Technische Vereisten: Computer of mobiel apparaat, Stabiele internetverbindingen Webbrowserzoals Chrome, Firefox, Safari of Edge.
Support of Ondersteuning: Helpdesk en online kennisbank 24/7
Certificering: Certificaat van deelname in PDF formaat
Prijs en Kosten: Cursusprijs zonder extra kosten
Annuleringsbeleid en Geld-Terug-Garantie: Wij beoordelen dit per situatie
Award Winning E-learning: Ja

Tip! Zorg voor een rustige leeromgeving, tijd en motivatie, audioapparatuur zoals een koptelefoon of luidsprekers voor audio, accountinformatie zoals inloggegevens voor toegang tot het e-learning platform.