- Course overview
- Course details
- Prerequisites
Course overview
About this course
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
• Data Scientists
Course details
Module 1: Course Introduction
• Define the course goal
• Recognize the course objectives
Module 2: AI Foundations
• Why AI?
• AI/ML framework on Google Cloud
• Google Cloud infrastructure
• Data and AI products
• ML model categories
• BigQuery ML
• Lab: BigQuery ML
Module 3: AI Development Options
• AI development options
• Pre-trained APIs
• Vertex AI
• AutoML
• Custom training
• Lab: Natural Language API
Module 4: AI Development Workflow
• ML workflow
• Data preparation
• Model development
• Model serving
• MLOps and workflow automation
• Lab: AutoML
• How a machine learns
Module 5: Generative AI
• Generative AI and workflow
• Gemini multimodal
• Prompt design
• Model tuning
• Model Garden
• AI solutions
• Lab: Vertex AI Studio
Prerequisites
- Basic knowledge of machine learning concepts
- Prior experience with programming languages such as SQL and Python
Enquiry
Course : Introduction to AI and Machine Learning on Google Cloud
Enquiry
request for : Introduction to AI and Machine Learning on Google Cloud
