[Free] Generative Ai Basics: Fundamentals To Real-World Impacts
Master Generative AI: Learn the Basics and Apply It to Real-World Solutions – Free Course
What you’ll learn
- Understand the core principles of Generative AI and how it differs from traditional AI models.
- Create and fine-tune basic prompts to generate text, images, or other media using AI tools.
- Apply Generative AI techniques to solve real-world problems across various industries.
- Explore the ethical considerations and impacts of using Generative AI in different applications.
Requirements
- No prior AI or programming experience needed – this course is designed for beginners.
- A basic understanding of general technology concepts is helpful but not required.
- Access to a computer with an internet connection for hands-on practice using AI tools.
- A willingness to learn and explore creative applications of AI technology.
Description
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:
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Lesson 1: Introduction to Generative AI
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Understand what Generative AI is and its key applications.
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Explore different types of Generative AI models and their challenges.
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Hands-on: Set up your environment to start building AI models.
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Lesson 2: Generative Adversarial Networks (GANs)
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Discover the architecture and training process of GANs for image generation.
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Hands-on: Implement and train your own GAN model.
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Lesson 3: Variational Autoencoders (VAEs)
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Learn how VAEs work, including their encoder-decoder structure and objective function.
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Hands-on: Build and apply VAE models to generate data.
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Lesson 4: Sequence Generation with Recurrent Neural Networks (RNNs)
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Master RNNs and LSTMs for text and sequence generation.
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Hands-on: Train RNN models for text generation tasks.
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Lesson 5: Transfer Learning in Generative AI
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Apply transfer learning principles to fine-tune pre-trained models for generative tasks.
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Hands-on: Use transfer learning in image and text generation.
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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.
Author(s): Tech Jedi