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Course Outline
Introduction to Vertex AI and Machine Learning Platforms
- Survey of artificial intelligence and machine learning workflows
- Familiarization with Google Cloud Vertex AI
- Comprehending the architecture and core components of Vertex AI
- Examining the contribution of Vertex AI to machine learning development and deployment
Establishing the Vertex AI Environment
- Setting up a Google Cloud project for Vertex AI
- Comprehending workspaces, resource allocation, and permission structures
- Arranging datasets and development environments
- Getting acquainted with Vertex AI tools and user interfaces
Machine Learning Fundamentals via Vertex AI
- Grasping the concepts of supervised learning
- Overview of regression and classification models
- Readying data for integration into machine learning workflows
- Assessing model performance and accuracy
Natural Language Processing (NLP) within Vertex AI
- Introduction to core NLP principles
- Understanding text-based machine learning applications
- Preparation and processing of text data
- Exploring the NLP features available in Vertex AI
Developing and Training Machine Learning Models
- Preparing training code specifically for Vertex AI
- Containerizing machine learning training applications
- Setting up training jobs
- Executing and overseeing model training processes
Deployment of Machine Learning Models
- Understanding the workflow for model deployment
- Creation of model endpoints
- Deploying trained models to generate predictions
- Administration of deployed models and associated resources
Monitoring and Troubleshooting Vertex AI Solutions
- Observing training and deployment activities
- Pinpointing frequent configuration challenges
- Resolving issues related to model execution
- Implementing best practices for dependable ML workflows
Practical Workshop and Course Summary
- Constructing an end-to-end machine learning workflow using Vertex AI
- Training and deploying a sample model
- Revisiting the primary features and capabilities of Vertex AI
- Discussing future steps for advanced machine learning development
Requirements
- Familiarity with machine learning concepts
Target Audience
- Software engineers
- Enthusiasts of machine learning
7 Hours
Testimonials (4)
easy steps in ML
John Erick Baltazar - Globe telecom
Course - Vertex AI
Got additional knowledge about Vertex AI/ML.
Jerico Torres - Globe telecom
Course - Vertex AI
Attends to the questions very well and explain things very well
Renzt Racela - Globe telecom
Course - Vertex AI
Overall, the training was very informative, the trainer provided different use case scenario and exercises so we can be familiarized with the Vertex AI application.