GenAI Foundations and AI Agents Development
This advanced course transforms you into an autonomous AI architect who builds intelligent agents that operate like digital team members.
Overview
This course includes:
- On-demand videos
- Practice assessments
- Multiple hands-on learning activities
- Exposure to a real-world project
- 100% self-paced learning opportunities
- Certification of completion
Ready to move beyond reactive AI systems to autonomous agents that think, plan, and execute complex tasks independently? Most AI implementations remain limited to simple question-and-answer interactions, missing the transformative potential of truly autonomous AI workers that can reason, collaborate, and solve problems without constant human guidance.
This advanced course transforms you into an autonomous AI architect who builds intelligent agents that operate like digital team members. You'll master the complete agent development lifecycle using cutting-edge frameworks like CrewAI, implement sophisticated tool integration that enables agents to interact with real-world systems, and design multi-agent orchestration where specialized agents collaborate to solve complex problems. Through intensive hands-on development, you'll create customer support agents with advanced reasoning capabilities, implement agent safety frameworks for production deployment, and build coordination systems that manage multiple autonomous agents working together.
By the end of this course, you'll confidently deploy agent systems that can handle multi-step reasoning scenarios, coordinate complex workflows between multiple specialized agents, and create customer support automation that rivals human-level service quality. You'll have the expertise to build the next generation of AI workers that are revolutionizing business operations worldwide.
Step into the future of autonomous AI and become the agent architect that organizations need to build truly intelligent, self-directed digital workers.
Skills You Will Gain
Learning Outcomes (At The End Of This Program, You Will Be Able To...)
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Construct robust data processing pipelines that transform raw data into AI-ready formats
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Implement advanced RAG architectures with component integration and performance optimization
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Develop customer support RAG systems with domain-specific knowledge base management
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Apply advanced retrieval strategies including metadata filtering, reranking, and quality enhancement
Prerequisites
Requires Python proficiency, understanding of databases and data processing, basic machine learning knowledge, and experience with APIs and web services.
Who Should Attend
Data engineers moving into AI, ML engineers focused on data pipelines, software engineers building knowledge systems, and AI/ML specialists implementing RAG solutions.
