
AI and ML Infrastructure Design
This course introduces the foundational concepts of AI/ML infrastructure, focusing on the key components and workflows needed to support AI/ML projects. Participants will learn the basics of data pipelines, model training, deployment strategies, and cloud-based AI tools. Through hands-on labs, learners will build and deploy simple AI/ML systems while gaining essential knowledge of storage, compute, and scalability in modern infrastructure.
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Course Duration:
24 hours
Level:
Beginner

Course Objectives
Understand the basic components of AI/ML infrastructure and workflows.
Learn how to manage and preprocess data for AI/ML models.
Deploy machine learning models using cloud-based tools and services.
Gain introductory knowledge of containerization and orchestration tools like Docker.
Develop a foundational understanding of AI/ML observability and monitoring.
Prerequisites
Basic programming knowledge, preferably in Python.
Familiarity with general IT infrastructure concepts (e.g., servers, storage, and networking).
No prior experience with AI/ML or cloud platforms is required.
