Google Gemini for Developers

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Lynn Langit

2:12:01

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01 - Introduction

01 - Build LLM-based applications with Google Gemini.mp4

00:49

02 - What you should know.mp4

01:14

03 - Using cloud services.mp4

01:24

02 - 1. Gemini Dev Environments

01 - Understanding Google Gemini.mp4

06:20

02 - Use Google AI Studio.mp4

04:10

03 - Use Vertex AI Studio.mp4

03:39

04 - Use Colab Notebooks.mp4

03:53

05 - Use Gemini Code Assist in cloud workstations.mp4

03:22

03 - 2. Gemini Prompts

01 - Use Google AI Studio to test prompts.mp4

05:28

02 - Use system instructions with prompts.mp4

03:07

03 - Design and test language model prompts.mp4

04:03

04 - Design and test multimodal prompts.mp4

02:44

05 - Design prompts in Cloud Code for APIs.mp4

05:56

04 - 3. Gemini Notebooks and APIs

01 - Using the Gemini API Set up.mp4

04:34

02 - Using the Gemini API Testing prompts.mp4

03:14

03 - Using function calling with Gemini.mp4

03:07

04 - Programming multimodal use cases.mp4

04:35

05 - Use the Gemini File API.mp4

04:04

06 - Use embeddings with Gemini.mp4

05:33

07 - Set up a RAG pattern with Gemini.mp4

09:53

08 - Implement a RAG pattern with Gemini.mp4

04:25

05 - 4. Gemini Model Evaluation

01 - Understand model grounding.mp4

03:38

02 - Ground a model with Google Search.mp4

04:42

03 - Ground with a semantic retriever.mp4

03:29

04 - Understand model evaluation.mp4

03:51

05 - Perform model evaluation.mp4

04:36

06 - Fine-tune a Gemini model.mp4

06:09

06 - 5. Gemini Applications

01 - Use Vertex AI Model Garden.mp4

06:31

02 - Deploy a GenAI cloud architecture Document summaries.mp4

04:49

03 - Deploy a GenAI cloud architecture Knowledge base.mp4

03:55

04 - Preview of Vertex AI Agent Builder.mp4

03:59

07 - Conclusion

01 - Next steps.mp4

00:48

Description

Google Gemini is a family of multimodal large language models that works seamlessly across image, video, audio, and code. In this course, instructor Lynn Langit shows you how to use Google Gemini design patterns, tools, and best practices for building LLM-based applications. These include patterns for requirements identification and design, which can include prompt engineering, RAG patterns, and fine-tuning. Learn about the capabilities of Google Gemini, starting with understanding the generative AI studio, and then diving into the development, evaluation, and deployment of models. And explore Gemini applications like the Vertex AI model garden and the Vertex AI agent builder.

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Artificial Intelligence

Lynn Langit

Instructor's Courses

Cloud Architect working with remote dev teams world-wide to build cloud solutions. Author of 30 LinkedIn Learning Cloud/Data courses with over 5 million student views. https://www.linkedin.com/learning/instructors/lynn-langit

Linkedin Learning

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LinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications. It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.