AI Development with Leading Platforms
Gain hands-on insight into leading AI development platforms — including Google Vertex AI, Azure Machine Learning, AWS SageMaker, and Databricks — and learn how they simplify the creation and deployment of machine learning solutions.
Duration:
Fees with SST:
1 Day
RM 1,620.00
AI is reshaping industries, but knowing where to begin can be overwhelming. This 1-day instructor-led course provides a high-level yet practical understanding of how the world’s top cloud platforms — Google Vertex AI, Microsoft Azure Machine Learning, AWS SageMaker, and Databricks — streamline AI development for both business and technical professionals.
Participants will explore the AI lifecycle (data preparation, model training, evaluation, and deployment) and discover how each platform supports innovation through managed services, scalability, and automation.
Through guided conceptual demonstrations, you’ll see how models can be built and deployed visually without extensive coding — making this the perfect first step into cloud-based AI development.
Module 1: Introduction to AI and Machine Learning
Understand what AI and ML are, including types like supervised, unsupervised, and reinforcement learning.
AI vs. ML vs. Deep Learning
The ML workflow: data preparation, feature engineering, model training, evaluation, and deployment
Module 2: Introduction to AI Development Platforms
Why cloud-based AI development? Scalability, managed infrastructure, and collaboration.
Overview of platforms:
Google Vertex AI – Integrated workflow, AutoML, MLOps
Microsoft Azure Machine Learning – Enterprise-ready designer interface and Azure integration
AWS SageMaker – Broad service coverage and community-driven tools
Databricks – Unified analytics, big data support, and MLflow integration
Comparison of services and features
Module 3: Conceptual Demonstrations (Hands-On Exploration)
Experience platform interfaces through guided visual demos.
Vertex AI: AutoML classification example
Azure ML: Drag-and-drop pipeline creation
SageMaker: Studio environment overview
Databricks: MLflow workspace and data integration
Module 4: Use Cases & Benefits
Explore real-world AI applications across industries — from finance and retail to healthcare and education.
Benefits of managed AI platforms: faster cycles, lower infrastructure costs, better collaboration
Introduction to MLOps for model monitoring and maintenance
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Frequently Asked Questions (FAQs)
Is this a coding course?
No. This is a conceptual and practical introduction focusing on workflows, not programming.
Will I use the platforms directly?
You’ll explore guided demonstrations and visual workflows, not hands-on coding.
Which platforms are covered?
Google Vertex AI, Microsoft Azure ML, AWS SageMaker, and Databricks.
Is this course suitable for non-technical professionals?
Yes. It’s designed for both technical and business roles.
Will I learn how to build AI models?
You’ll understand the conceptual process and workflows involved in building and deploying models.