Naif-Ganadily / GenerativeAI_for_Developers_Google_Cloud

Generative AI for Developers Learning Path Documentation

Courses Overview

1. Introduction to Image Generation

• Description: Introduction to diffusion models and their significance in the realm of image generation, focusing on their application within Google Cloud's Vertex AI.
• Components: 1 Video, 1 Quiz.

2. Attention Mechanism

• Description: Exploration of the attention mechanism, understanding its ability to improve neural network performances across various tasks such as machine translation, text summarization, and question answering.
• Duration: Approximately 45 minutes.
• Components: 1 Video, 1 Quiz.

3. Encoder-Decoder Architecture

• Description: Comprehensive coverage of the encoder-decoder architecture, its relevance to sequence-to-sequence tasks, and hands-on TensorFlow coding for poetry generation.
• Components: 2 Videos, 1 Link, 1 Quiz.

4. Transformer Models and BERT

• Description: Insights into the Transformer architecture and the BERT model, including the self-attention mechanism and its applications in text classification, question answering, and more.
• Duration: Approximately 45 minutes.
• Components: 2 Videos, 1 Link, 1 Quiz.

5. Create Image Captioning Models

• Description: Instruction on building image captioning models using deep learning techniques, emphasizing encoder and decoder components, training, and evaluation.
• Components: 2 Videos, 1 Link, 1 Quiz.

6. Introduction to Generative AI Studio

• Description: An introductory course on Generative AI Studio on Vertex AI, highlighting its features, options, and hands-on application through product demos.
• Components: 1 Video, 1 Link, 1 Document, 1 Quiz.

7. Generative AI Explorer - Vertex Quest

• Description: A practical exploration into the use of Generative AI on Google Cloud, focusing on the Vertex AI PaLM API family, prompt design, best practices, model tuning, and deployment.
• Components: Lab exercises.

8. Explore and Evaluate Models using Model Garden

• Description: Guidance on utilizing Model Garden on Vertex AI to search, discover, and interact with models from Google and its partners, including experimentation with Generative AI Studio.
• Components: Interactive Labs.

9. Prompt Design using PaLM

• Description: A deep dive into the art and science of prompt design for large language models (LLMs) like PaLM, tailored to generate desired outputs across various applications.
• Scenario: Role-play as a marketing analyst for real estate, focusing on creating prompts for summarizing extensive home descriptions.
• Components: Hands-on Lab.

Bonus Lab. GenerativeAI for Video Analytics with Vertex AI

• Successfully completed the lab, gaining hands-on experience with LangChain applications for processing and analyzing video content through natural language tasks.
• Explored the documentation for Generative AI on Vertex AI and the Google Cloud Tech YouTube channel for further learning.
• Considered pursuing Google Cloud training and certification to deepen understanding of cloud technologies and applications in natural language processing.