The Team – WebStory24.com

9 Free Google Courses that Will Make You an AI Expert

Understand the basic concepts of generative AI, including its history and evolution. Explore real-world applications of generative AI, such as image - text generation, music composition, and drug discovery.

1. Introduction to Generative Artificial Intelligence

Understand the ethical implications of AI, including bias, fairness, and privacy concerns. Explore the role of AI in social good and its potential to address global challenges.

2. Responsible Artificial Intelligence

Learn about the architecture and training of large language models like GPT-3. Understand the capabilities and limitations of these models, including their ability to generate text, translate languages, and answer questions.

3. Large Language Model

Understand the basic architecture of encoder-decoder models. Learn how encoder-decoder models are used in various tasks, such as machine translation, text summarization, and image captioning.

4. Encoder-Decoder Architecture

Dive deep into the architecture of transformer models, including self-attention and positional encoding. Learn about the BERT model and its applications in natural language understanding and generation.

5. Transformer and BERT Model

Understand the concept of attention and its role in improving the performance of neural networks. Learn about different types of attention mechanisms, such as self-attention and cross-attention.

6. Attention Mechanism

Learn how to use Google's user-friendly tool to create and experiment with generative AI models. Explore the different features and capabilities of the studio. Understand the underlying techniques used by the studio.

7. Generative AI Studio

Learn about different techniques for generating realistic images, such as GANs and VAEs. Explore the applications of image generation in various fields, including art, design, and gaming.

8. Image Generation

Learn about the techniques used for image classification and object detection. Explore the applications of image recognition in various fields such as self-driving cars, medical image analysis, and security.

9. Image Recognition

Thank you for reading!

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