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Introduction to AI and machine learning on Google Cloud
- Categories:
- Artificial Intelligence Cloud
- Level:
- Intermediate
- Code:
- GCPAIML
- Exam:
- Not Applicable
Overview
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.
Products covered:
- Vertex AI
- Gemini multimodal
- AutoML
- BigQuery ML
- Vertex AI Pipelines
- TensorFlow
- Model Garden
- Vertex AI Studio
- Natural Language API
- Contact Center AI (CCAI)
Prerequisites
Having one or more of the following:
- Basic knowledge of machine learning concepts
- Prior experience with programming languages such as SQL and Python
Who this course is for?
Professional AI developers, data scientists, and ML engineers who want to build predictive and generative AI projects on Google Cloud.
What's included
Select your preferred way to learn:
What is Virtual?
Live, instructor-led training delivered online
Interactive online sessions led by subject matter experts. Learners join live classes, take part in discussions, and complete practical exercises from any location, making it easy to fit collaborative learning into busy schedules.
If you prefer to connect to a course that is taking place in a physical classroom, you can choose our Remote Access option. .
Best for: Teams and individuals who want expert guidance, real-time collaboration, and flexible access.
What's included?
1 Day instructor led course
Exam: Not Applicable
6 month free access to QA learning platform
Free 6-Month Access: Learning Platform Discovery plan
Included FREE with every instructor‑led course
Get free guided access to the QA Learning Platform. Assess your skills, explore in-demand topics, and understand which areas to focus on.
Learn AI, Cloud, Data, and Leadership skills at your own pace.
Put skills into practice with hands-on Labs and Simulabs.
Validate knowledge and highlight gaps with skills assessments.
What is bespoke training?
Custom instructor-led training designed by QA to fit your needs
Tailored programmes built around your organisation’s goals, challenges, and skill levels. Delivered in the format that suits you to maximise relevance and impact.
Best for: Organisations and teams looking to target specific business priorities and capabilities with QA subject matter expertise.
Find out more about the course:
Learning outcomes
- 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.
Course outline
Module 1: AI Foundations
Topics
Why AI?
- AI/ML framework on Google Cloud
- Google Cloud infrastructure
- Data and AI products
- ML model categories
- BigQuery ML
- Lab introduction: BigQuery ML
Activities
- Lab: Predicting Visitor Purchases with BigQuery ML
- Quiz
- Reading
Module 2: AI Development Option
Topics
- AI development options
- Pre-trained APIs
- Vertex AI
- AutoML
- Custom training
- Lab introduction: Natural Language API
Module 3: AI Development Workflow
Topics
- ML workflow
- Data preparation
- Model development
- Model serving
- MLOps and workflow automation
- Lab introduction: AutoML
- How a machine learn
Activities
- Lab: Vertex AI: Predicting Loan Risk with AutoML
- Quiz
- Reading
Module 4: Generative AI
Topics
- Generative AI and workflow
- Gemini multimodal
- Prompt design
- Model tuning
- Model Garden
- AI solutions
- Lab introduction: Vertex AI Studio
Activities
- Lab: Getting Started with Vertex AI Studio
- Quiz
- Reading
Module 5: Course Summary
- Recognize the primary concepts, tools, technologies, and products learned in the course
Good to know
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Certificates of Achievement are issued at the end the course, either as a hard copy or via email. Read more here.