베스트 AI 자격증 | 구글 Generative AI Leader

2026.01.30 / JUN.NXP

저는 지난 12월의 AWS AIF 인증자격 스터디에 이어 1월엔 GCP Generative AI Leader 인증자격 스터디를 진행중입니다. 1월말에 우연히 참석한 GCP APAC 클라우드 테크 세미나에서 GCP ADK, A2A 핸즈온을 하면서 제 업무를 기준으로 한 GCP의 유용성을 확인할 수 있었고요, Generative AI Leader 인증자격에 시간과 비용을 투자할만 하다는 생각이 들었습니다.

최근 몇 달간 AI 수요에 맞춰 다양한 콘텐츠를 기획하고 바이브코딩 실험을 지속하면서 AI 기술 활용에 대한 좀 더 올바른 방향, 글로벌 표준으로 일컬을 수 있는 기준을 찾고 있었는데요, Generative AI Leader 과정을 수강하면서 구글이 제안하는 AI 기술 기획의 원칙 또는 표준을 실무적으로 파악할 수 있어서 좋습니다.

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서론: 구글 Generative AI Leader 자격시험 개요

• Generative AI Leader는 생성형 AI의 기능을 명확히 설명하고 이러한 기능이 조직에 어떤 이점을 제공하는지 이해할 수 있습니다.
• 온디맨드 과정 모음을 통해 학습자는 생성형 AI에 대한 전반적인 개요를 얻고 조직 혁신을 위해 생성형 AI와 Google Cloud를 활용하는 방법을 이해하게 됩니다.
• 흥미로운 동영상과 대화형 구성요소를 사용하여 생성형 AI에 대해 알아보고 Gemini Advanced, NotebookLM, Google AI Studio와 같은 도구를 사용한 실습을 통해 실무 경험을 쌓을 수 있습니다.

Generative AI Leader 소개 영상

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시험 정보

시험응시 | GCP Generative AI Leader
https://cloud.google.com/learn/certification/generative-ai-leader

시험개요

• 90분, 객관식 50~60문항
• 응시료 $99 (나는 $60)
• 영어 지문, 온라인 감독관

샘플문항 | Generative AI Leader Sample Questions
https://docs.google.com/forms/d/e/1FAIpQLScNn5oUIFeMQjtsHilQsJPxDsnP-0DbhDVsIXaBeCmPj-dgYw/viewform

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시험 준비

강의코스 | Google Skills: Paths – Generative AI Leader
https://www.skills.google/paths/1951

이번 패스를 구성하는 5개 코스

1. 1.5H / Gen AI: Beyond the Chatbot
2. 1.0H / Gen AI: Unlock Foundational Concepts
3. 1.2H / Gen AI: Navigate the Landscape
4. 1.8H / Gen AI Apps: Transform Your Work
5. 2.2H / Gen AI Agents: Transform Your Organization

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코스 샘플 퀴즈 예시

Gen AI: Beyond the Chatbot 코스에 포함된 샘플 퀴즈

C1 Quiz

C1.1 Which of the following statements accurately describe Gemini? Select two.

1. Gemini is a type of generative AI specifically designed for generating images.
2. Gemini is a generative AI model (or family of models) developed by Google.
3. Gemini is a chatbot that can answer questions and generate creative content.
4. Gemini is an AI assistant that can help you be more creative and productive.
5. Gemini is a type of artificial intelligence that can create new content, including text, images, music, and even code.

C1.2 Which of the following describes a multimodal gen AI application?

1. Using NotebookLM Business to summarize a financial report.
2. Using gen AI to analyze customer sentiment in video testimonials and survey data.
3. Using Gemini in Gmail to write an email.
4. Using Imagen to create an image for a website.

C1.3 A CEO is hesitant to invest in generative AI because they believe it’s just a technology for building chatbots. Which of the following statements would BEST demonstrate that generative AI can offer their business much more?

1. Counting the number of website visitors and their locations.
2. Creating photorealistic images of new product prototypes based on text descriptions.
3. Providing generic responses to all customer inquiries, regardless of the specific issue.
4. Scheduling meetings and managing calendars to help employees improve their time management.

C1.4 Which of the following BEST defines generative AI?

1. A type of artificial intelligence that focuses on automating repetitive tasks and improving efficiency.
2. A type of artificial intelligence that analyzes existing data to identify patterns and make predictions.
3. A type of artificial intelligence that can create new content, including images, text and music.
4. A specific application, like a chatbot, that utilizes AI technology.

C2 Quiz

C2.1 What is the purpose of a prompt in the context of foundation models?

1. To train the model on new data.
2. To fine-tune the model for a specific task.
3. To evaluate the model’s performance.
4. To provide input to the model and trigger an output.

C2.2 Which of the following is NOT a key feature of foundation models?

1. Specialized to specific tasks.
2. Trained on diverse data.
3. Flexible to support various use cases.
4. Adaptable to new domains and tasks.

C2.3 What is the primary difference between foundation models and traditional AI models?

1. Foundation models are trained on massive amounts of diverse data for various tasks, while traditional models are trained on specific data for a single task.
2. Foundation models cannot be adapted to new tasks, while traditional models can.
3. Foundation models are trained on specific data for a single task, while traditional models are trained on diverse data for various tasks.
4. Foundation models are only trained on text data, while traditional models use images and code.

C2.4 How do foundation models and prompt engineering work together to create value in generative AI?

1. Foundation models offer a vast knowledge base, and prompt engineering guides the model to use this knowledge in responses.
2. Foundation models ensure the ethical use of generative AI, while prompt engineering focuses on improving the quality and creativity of outputs.
3. Foundation models provide the computing power for generative AI, while prompt engineering directs that power to complete specific tasks.
4. Prompt engineering trains foundation models on specific tasks, allowing them to generate highly specialized content and insights.

C2.5 Which of the following best defines a foundation model?

1. Hardware infrastructure used to train and deploy AI models.
2. Small, very specialized AI models trained on narrow datasets in order to perform specific tasks.
3. Traditional machine learning algorithms that rely on explicitly defined rules.
4. Large AI models trained on a vast quantity of data, capable of adapting to a variety of tasks.

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참고: 자격인증서 예시

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첫 포스팅: 2026.01.30 / 포스트 문의: JUN.NXP (naebon@naver.com)