Introduction to AI and Machine Learning on Google Cloud
- Kursuskode GO9095
- Varighed 1 Dag
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Åbent kursus (Virtuelt)
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Beskrivelse
ToppenThis 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:
- Gemini multimodal
- Gemini Enterprise
- NotebookLM
- BigQuery ML
- Vertex AI, Vertex AI Studio, Vertex AI Agent Builder, Vertex AI Pipelines
- Natural Language API
- AutoML
Updated July 2026
Virtuel deltagelse
Et V&C Select kursus indholder nøjagtig det samme som et almindeligt kursus. Før kursusstart modtager man kursusmaterialet. Dernæst logger man på kurset via internettet og ser via sin pc den selvsamme præsentation som de øvrige deltagere, man kommunikerer via chat med underviseren og de øvrige deltagere på kurset. Denne uddannelsesmodel er både tids-og omkostningsbesparende og kan være et oplagt alternativ til almindelig klasseundervisning, hvis man f.eks. har et begrænset rejsebudget.
Kursusdato
ToppenMålgruppe
ToppenKursets formål
ToppenAfter this course participants should be able to:
- 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.
Kursusindhold
ToppenModule 0: Course Introduction
- Define the course objectives.
- Recognize the course structure
Module 1: AI Foundations
- Recognize the AI/ML framework on Google Cloud.
- Identify the major components of AI infrastructure.
- Define the data and ML products on Google Cloud and how they support the data-to-AI lifecycle.
- Build an ML model with BigQuery ML to bring data to AI.
- Lab: Predict Visitor Purchases with BigQuery ML
Module 2: Generative AI
- Define generative AI and foundation models.
- Recognize the prompt-to-production lifecycle and its associated tools.
- Define AI agents and their core components.
- Identify Google Cloud tools and technologies for building AI agents.
- Lab: Get started with Vertex AI Studio
Module 3: AI Development Options
- Define different options to build an ML model with Vertex AI on Google Cloud.
- Identify the features and use cases of pre-trained APIs, AutoML, and custom training.
- Use the Natural Language API to analyze text.
- Lab: Entity and Sentiment Analysis with Natural Language API
Module 4: 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 with Vertex AI.
- Lab: Vertex AI: Predict Loan Risk with AutoML
Module 5: Course Summary
- Recognize the primary concepts, tools, technologies, and products learned in the course.
Forudsætninger
ToppenHaving one or more of the following:
- Basic knowledge of machine learning concepts
- Prior experience with programming languages such as SQL and Python
Certificeringstest
ToppenNone
Efterfølgende kurser
ToppenNo recommendation
Mere information
Toppen- Official course book provided to participants
