Agentic AI Content for Practitioners (Teams: Data)

Overview

Agentic AI Content for Practitioners (Teams: Data) is an intermediate-level course designed to equip data professionals, software engineers, and business analysts with the knowledge and skills to design, implement, and optimize AI agents for intelligent data automation. As organizations transition from experimental AI deployments to enterprise-scale implementations, this course provides the practical expertise needed to build reliable, scalable agent systems that deliver measurable business value. Through hands-on labs, real-world case studies, and interactive projects, you'll learn to transform manual data operations into intelligent, adaptive systems. The course covers everything from agent architecture fundamentals to advanced optimization strategies, preparing you to lead AI agent initiatives in your organization. You'll explore popular frameworks, design patterns, and deployment strategies while addressing critical considerations like error handling, scalability, and enterprise integration. Whether you're automating data quality monitoring, building predictive analytics systems, or creating intelligent customer service agents, this course provides the foundation you need to succeed in the rapidly evolving landscape of AI-powered data automation.

Syllabus

Lesson 1: Analyze AI Agents: Architecture, Types, and Data Automation Fundamentals

This foundational lesson introduces learners to the core concepts of AI agents, their architectural components, and their specific applications in data automation. Through real-world examples and hands-on exploration, learners will understand what makes AI agents effective for automating data workflows and identify key use cases across industries.

Lesson 2: Implementing AI Agents for Data Workflows

This lesson focuses on practical implementation of AI agents for data automation. Learners will explore popular frameworks, design patterns, and deployment strategies. Through hands-on labs and case studies, they'll learn to build, test, and deploy AI agents for real-world data workflows while addressing common challenges like error handling, scalability, and integration with existing systems.

Lesson 3: Optimizing and Scaling AI Agent Systems

This final lesson focuses on advanced topics in AI agent deployment, including performance optimization, scalability strategies, and enterprise integration. Learners will explore monitoring and evaluation frameworks, learn to scale agent systems for production environments, and develop strategies for continuous improvement and maintenance. The lesson culminates in a comprehensive capstone project and assessment.