Introduction to AI and Machine Learning on Google Cloud
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03 Jun 2024 - 03 Jun 2024 | Introduction to AI and Machine Learning on Google Cloud |
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09 Sep 2024 - 09 Sep 2024 | Introduction to AI and Machine Learning on Google Cloud |
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04 Nov 2024 - 04 Nov 2024 | Introduction to AI and Machine Learning on Google Cloud |
Description
This course introduces the AI and machine learning (ML) offerings on Google Cloud that build both predictive and generative AI projects. It explores the technologies, products, and tools available throughout the data-to-AI life cycle, encompassing AI foundations, development, and solutions. It aims to help data scientists, AI developers, and ML engineers enhance their skills and knowledge through engaging learning experiences and practical hands-on exercises.
Audience and prerequisites
This class is intended for the following job roles:
- Professional AI developers, data scientists, and ML engineers who want to build predictive and generative AI projects on Google Cloud.
Prerequisites:
To get the most out of this course, participants should have one or more of the following:
- Basic knowledge of machine learning concepts.
- Prior experience with programming languages such as SQL and Python.
Objectives
This course teaches participants the following skills:
- Recognize the data-to-AI technologies and tools provided by Google Cloud.
- Build generative AI projects by using Gemini multimodal, efficient prompts, and model tuning.
- Explore various options for developing an AI project on Google Cloud.
- Create an ML model from end-to-end by using Vertex AI.
Topics
Course Introduction.
- Define the course goal.
- Recognize the course objectives.
AI Foundations.
- Recognize the AI/ML framework on Google Cloud.
- Identify the major components of Google Cloud infrastructure.
- Define the data and ML products on Google Cloud and how they support the data-to-AI lifecycle.
- Build an ML model with BigQueryML to bring data to AI.
AI Development Options.
- Define different options to build an ML model on Google Cloud.
- Recognize the primary features and applicable situations of pre-trained APIs, AutoML, and custom training.
- Use the Natural Language API to analyze text.
AI Development Workflow.
- Define the workflow of building an ML model.
- Describe MLOps and workflow automation on Google Cloud.
- Build an ML model from end-to-end by using AutoML on Verex AI.
Generative AI.
- Define generative AI and foundation models.
- Use Gemini multimodal with Verex AI Studio.
- Design efficient prompt and tune models with different methods.
- Recognize the AI solutions and the embedded Gen AI features.
Open calls
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03 Jun 2024 - 03 Jun 2024 | Introduction to AI and Machine Learning on Google Cloud |
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09 Sep 2024 - 09 Sep 2024 | Introduction to AI and Machine Learning on Google Cloud |
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04 Nov 2024 - 04 Nov 2024 | Introduction to AI and Machine Learning on Google Cloud |
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27 Jan 2025 - 27 Jan 2025 | Introduction to AI and Machine Learning on Google Cloud |
