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Curriculum Designed by Experts

Generative Adversarial Networks (GAN) - Essentials Corporate Training by Multisoft Virtual Academy is a specially designed program for organizations aiming to strengthen their AI and machine learning capabilities. This course introduces your team to the core concepts of GANs, including generator-discriminator dynamics, training strategies, loss functions, and real-world applications such as image generation and data augmentation.
Delivered by certified industry experts, the training emphasizes practical learning with hands-on labs, project-based assignments, and interactive live sessions. Whether your team is from a tech, analytics, or research background, this course simplifies complex GAN concepts for easy understanding and implementation. By the end of the course, your workforce will be equipped with the knowledge to build and experiment with basic GAN models and understand how GANs are shaping the future of AI.
Generative Adversarial Networks (GAN) – Essentials training is a foundational course designed to introduce learners to the core principles, architecture, and applications of GANs in artificial intelligence. It covers how GANs work using generator and discriminator models, explores real-world use cases, and includes hands-on practice with tools like TensorFlow or PyTorch. Ideal for beginners, this course builds essential skills for implementing GANs in deep learning projects.
- What is Generative Models?
- Application of Generative Models
- Types of Generative Models
- Magenta Sketch-RNN

- What is Deep Dream?
- DeepDream Applications
- How Deep Dream Work?
- Implementation of Deep Dream on Tensorflow 2.x

- What is Neural Style Transfer?
- Fast Style Transfer using TF-Hub
- Implementation of Neural Style Transfer on Tensorflow 2.x

- What is Autoencoder?
- Variational Autoencoder (VAE)
- VAE Implementation on Tensorflow 2.x

- Introduction to GAN
- GAN Applications
- Basic DC GAN Architecture
- Discriminator and Generator Loss
- DCGAN Implementation on Tensorflow 2.x
- GAN Challenges and Tricks

- Introduction to C-GAN
- Image to Image Translation & Pix2Pix
- Pix2Pix implementation on Tensorflow 2.x

- Introduction to CycleGAN
- Cycle Consistency Loss
- CycleGAN implementation on Tensorflow 2.x

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Generative Adversarial Networks (GAN) - Essentials Corporate Training Certification
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