Discover the power of Generative AI with this comprehensive beginner-friendly course! You’ll start with the fundamentals of Generative AI and explore its wide-ranging applications across industries. Through practical, hands-on exercises, you’ll learn to build AI models like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Recurrent Neural Networks (RNNs) to generate images, text, and more.

What you’ll learn:

• Lesson 1: Introduction to Generative AI

  • Understand what Generative AI is and its key applications.

  • Explore different types of Generative AI models and their challenges.

  • Hands-on: Set up your environment to start building AI models.

• Lesson 2: Generative Adversarial Networks (GANs)

  • Discover the architecture and training process of GANs for image generation.

  • Hands-on: Implement and train your own GAN model.

• Lesson 3: Variational Autoencoders (VAEs)

  • Learn how VAEs work, including their encoder-decoder structure and objective function.

  • Hands-on: Build and apply VAE models to generate data.

• Lesson 4: Sequence Generation with Recurrent Neural Networks (RNNs)

  • Master RNNs and LSTMs for text and sequence generation.

  • Hands-on: Train RNN models for text generation tasks.

• Lesson 5: Transfer Learning in Generative AI

  • Apply transfer learning principles to fine-tune pre-trained models for generative tasks.

  • Hands-on: Use transfer learning in image and text generation.

By the end of this course, you will have the knowledge and practical skills to apply Generative AI models in real-world projects. This course is perfect for beginners looking to dive into the exciting field of AI and professionals wanting to expand their expertise in AI-powered creativity.

Who this course is for:

• Beginners curious about Generative AI who have no prior experience but want to explore its fundamentals.
• Tech enthusiasts eager to understand how AI is transforming industries and real-world applications.
• Creatives and innovators looking to leverage AI for generating content, art, or other media.
• Professionals and students interested in AI technologies and their practical impact on fields like design, marketing, and content creation.