| 1. Best Practices.mp4 | 19.5 MB | ||
| 1. Foundational Models on Google Gemini.mp4 | 18.6 MB | ||
| 1. Introduction to Building Generative AI Applications with Gemini.mp4 | 24.7 MB | ||
| 1. Introduction to Creating a Context-Driven Chatbot with Gemini.mp4 | 24.1 MB | ||
| 1. Introduction to the Course.mp4 | 32 MB | ||
| 1. Understanding Why we Use the API.mp4 | 8.5 MB | ||
| 1. Wrap-Up.mp4 | 27.8 MB | ||
| 2. Building the Backend of an AI Application.mp4 | 13.5 MB | ||
| 2. Demo of our AI Application.mp4 | 6 MB | ||
| 2. Installing Python and Jupyter Notebook.mp4 | 47 MB | ||
| 2. Prerequisites for the Course.mp4 | 8.8 MB | ||
| 2. Pricing.mp4 | 27.5 MB | ||
| 2. Using Google Bard with Gemini.mp4 | 69.8 MB | ||
| 2. Working with a Chatbot with Context on Google Gemini.mp4 | 27.4 MB | ||
| 3. Building the Frontend of an AI Application.mp4 | 13 MB | ||
| 3. Challenges.mp4 | 12.2 MB | ||
| 3. Final Exam.html | 102.4 B | ||
| 3. Introduction to Using the Google Vertex AI Studio Playground for Gemini.mp4 | 89.6 MB | ||
| 3. Performing Text Generation using the Gemini API.mp4 | 38.3 MB | ||
| 3. Safety Ratings on Gemini.mp4 | 103.6 MB | ||
| 3. What is Google Gemini.mp4 | 33.3 MB | ||
| 3.1 Text Generation.ipynb | 24.2 KB | ||
| 3.1 Working with Safety Ratings on Gemini.ipynb | 15.8 KB | ||
| 4. A Demo of the Application.mp4 | 6 MB | ||
| 4. Design and Develop a Recipe Recommendation Chatbot App.html | 102.4 B | ||
| 4. Introduction to Retrieval Augmented Generation.mp4 | 35.5 MB | ||
| 4. Parameters and Considerations.mp4 | 21.2 MB | ||
| 4. Using Parameters within Text Generation.mp4 | 40.8 MB | ||
| 4. Where to Go from Here.mp4 | 7.8 MB | ||
| 4. Which Google product is the first to be engineered for Gemini Nano.html | 102.4 B | ||
| 5. Caution on Using LLMs.mp4 | 24.9 MB | ||
| 5. End of Section 5 Quiz.html | 102.4 B | ||
| 5. End of Section 6 Quiz.html | 102.4 B | ||
| 5. Introduction to Image Generation on Gemini.mp4 | 20.6 MB | ||
| 5. Setting Up Documents and Libraries for RAG with Gemini API.mp4 | 208.8 MB | ||
| 5.1 Retrieval Augmented Generation with Gemini.ipynb | 49.4 KB | ||
| 6. Crafting Your Initial Prompt.mp4 | 41.7 MB | ||
| 6. Generating Code with the Gemini API.mp4 | 29.7 MB | ||
| 6. Performing Text Searches with RAG on Gemini.mp4 | 32.2 MB | ||
| 7. End of Section 1 Quiz.html | 102.4 B | ||
| 7. Performing Image Generation using the Gemini API.mp4 | 111.9 MB | ||
| 7. Searching for Images through RAG on Gemini.mp4 | 78.4 MB | ||
| 7.1 Gemini with Vision.ipynb | 1.4 MB | ||
| 8. End of Section 3 Quiz.html | 102.4 B | ||
| 8. Implementing RAG the Multimodal Way.mp4 | 109.8 MB | ||
| 9. End of Section 4 Quiz.html | 102.4 B | ||
| Bonus Resources.txt | 409.6 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 48 total files | |||
Google Gemini AI Masterclass: The Ultimate Guide
https://DevCourseWeb.com
Published 12/2023
Created by Renaldi Gondosubroto
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 34 Lectures ( 3h 52m ) | Size: 1.4 GB
From Basic to Advanced Generative Artificial Intelligence on Google Gemini
What you'll learn
Acquire a comprehensive understanding of Google Gemini AI and its integration with Google Cloud services to deploy generative AI applications.
Gain proficiency in utilizing the Google Gemini API to access and interact with the family of foundational models within it.
Master the techniques of prompt engineering to effectively communicate with Gemini Pro and obtain desired responses for various AI applications.
Develop skills to customize, build, and scale generative AI applications using Gemini Pro, ensuring privacy and without managing infrastructure.
Requirements
Proficiency in Python programming is essential.
A foundational understanding of artificial intelligence and machine learning concepts will be beneficial to grasp the advanced topics covered in the course.
A computer with internet access to utilize Google Cloud's services and to participate in the online course.
A Google Cloud account to practice and apply the concepts learned in the course.
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