Training goals

code: GC-WEPGAI | version: v1.0

As generative AI becomes more common, the ability to interact with large language models is shifting from niche knowledge to a necessary skill across many different industries and roles. In this course, you will learn the fundamentals of prompting large language models and exploring further techniques for improving the output from large language models. You will also explore similar concepts when working with multimodal models such as Gemini Vision Pro.

What you'll learn:

Understand the basics of generative AI and how it compares to traditional AI.
Design effective prompts following general best practices.
Improve large language model outputs using easy-to-approach prompt engineering techniques.
Write effective prompts for interacting with multimodal models such as Gemini Vision Pro.

Conspect Show list

Module 1 - Understanding Generative AI
- Topics:
  - Gen AI vs. AI/ML
  - Gen AI Applications
  - Business Impact of Gen AI
- Objectives:
  - Define generative AI as a subset of AI.
  - Discuss the potential impact of AI on organizations .
  - Provide examples of generative AI applications.
Module 2 - Prompt Design
- Topics:
  - Prompt content types.
  - Prompt design strategies.
  - Iterating prompts for improvement.
- Objectives:
  - Understand the role of context and examples in prompts.
  - Iterate on prompts to improve model output.
- Activities:
  - Lab: Introduction to Prompt Design
Module 3 - Improving Prompts
- Topics:
  - Prompt design versus prompt engineering
  - Zero-shot and few-shot prompting
  - Chain-of-thought prompting
  - Overview of additional techniques
- Objectives:
  - Describe the difference between prompt design and prompt engineering.
  - Write prompts using few-shot and chain-of-thought techniques.
  - Learn about additional prompt engineering techniques being used today.
- Activities:
  - Lab: Improving your Prompts
Module 4 - Working with Multimodal Models
- Topics:
  - What is a multimodal model?
  - Prompt design strategies
  - Best practices for multimodal prompts
  - Troubleshooting your multimodal prompt
- Objectives:
  - Understand the multimodal models and their use cases.
  - Design effective prompts for multimodal models.
- Activities:
  - Lab: Writing Prompts for Gemini Pro Vision

Download conspect training as PDF

Additional information

Prerequisites	There are no prerequisites for this course. The workshop aims to provide both introductory and advanced insights into Gen AI, making it suitable for individuals with varying levels of AI expertise.
Difficulty level
Duration	1 day
Certificate	The participants will obtain certificates signed by Google Cloud
Trainer	Authorized Google Cloud Trainer.

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duration: 1 day

difficulty level: 4 of 6

code: GC-VAIMLP

version: v1.0

price from: 2300 EUR

duration: 5 days

difficulty level: 4 of 6

code: G-MLGC

version: v4.0

price from: 600 EUR

duration: 1 day

difficulty level: 3 of 6

code: G-IRAIP

version: v1.0

price from: 600 EUR

duration: 1 day

difficulty level: 3 of 6

code: GC-IUCGAI

version: v1.0

price from: 600 EUR

duration: 1 day

difficulty level: 1 of 6

code: GC-EDMGAI

version: v1.0

price from: 600 EUR

duration: 1 day

difficulty level: 3 of 6

code: GC-IAIMLGC

version: 2.0

price from: 600 EUR

duration: 1 day

difficulty level: 3 of 6

code: GC-IDEGGC

version: 1.0

price from: 600 EUR

duration: 1 day

difficulty level: 3 of 6

code: GC-ADLLMGC

version: 1.0

price from: 600 EUR

duration: 1 day

difficulty level: 3 of 6

code: GC-VAIAB

version: 1.0

price from: 1500 EUR

duration: 3 days

difficulty level: 3 of 6

code: G-ADWCR

price from: 600 EUR

duration: 1 day

difficulty level: 3 of 6

code: G-IRAIP

version: v1.0

price from: 600 EUR

duration: 1 day

difficulty level: 3 of 6

code: GC-IUCGAI

version: v1.0

price from: 1000 EUR

duration: 2 days

difficulty level: 3 of 6

code: GC-GSFOGC-FOP

version: v1.0

price from: 2300 EUR

duration: 5 days

difficulty level: 3 of 6

code: AZ-204T00

version: A

price from: 1900 EUR

duration: 4 days

difficulty level: 3 of 6

code: AZ-220T00

version: A