Agentic AI Systems Architect

Master the design, implementation, and deployment of sophisticated agentic AI systems

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Course Overview

This comprehensive course is designed to equip participants with the knowledge, skills, and practical experience needed to design, implement, and deploy sophisticated agentic AI systems. Through a structured curriculum spanning ten modules, students will progress from foundational concepts to advanced implementation techniques, culminating in a capstone project that demonstrates mastery of agentic AI architecture.

🎯 Target Audience

Software engineers looking to specialize in AI agent development
AI/ML practitioners transitioning to agent-based systems
Technical architects designing autonomous AI solutions
Technical leaders responsible for AI strategy and implementation
Researchers exploring practical applications of agentic AI

🧠 Prerequisites

Intermediate programming skills (Python recommended)
Basic understanding of machine learning concepts
Familiarity with cloud computing fundamentals
Experience with API integration and web services
Understanding of software architecture principles

🚀 Learning Outcomes

By the end of this course, you will be able to:

Design comprehensive architectures for agentic AI systems
Implement and integrate the core components of AI agents
Select appropriate data structures and knowledge representation formats
Apply various planning and decision-making algorithms
Utilize modern agent development frameworks effectively
Design and implement multi-agent systems with effective coordination
Deploy agent systems on scalable cloud infrastructure
Implement security controls and ethical guidelines
Optimize performance and resource utilization
Build end-to-end agentic AI solutions for real-world problems

Need custom AI solutions? Check out AIVibes Consulting

Course Structure

Module 1

Foundations of Agentic AI Systems

Core concepts, historical evolution, and key capabilities of agentic AI systems.

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Module 2

Architectural Components

Perception, cognition, action, and memory modules that form the building blocks of agentic systems.

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Module 3

Data Structures and Knowledge Representation

Knowledge graphs, vector embeddings, and memory models for agent knowledge.

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Module 4

Planning and Decision-Making Algorithms

Symbolic planning, reinforcement learning, and search algorithms for agent decision-making.

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Module 5

Agent Development Frameworks and Tools

LangChain, AutoGen, LlamaIndex, and other frameworks for building agents.

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Module 6

Multi-Agent Systems Design

Coordination, communication, and emergent behaviors in multi-agent systems.

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Module 7

Cloud Infrastructure for Agentic AI

Deployment architectures, databases, and scaling patterns for agent systems.

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AIVibes Cloud Solutions

Module 8

Security, Governance, and Responsible AI

Sandboxing, access control, and ethical considerations for agentic systems.

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Module 9

Performance Optimization and Scaling

Benchmarking, caching strategies, and resource allocation for efficient agents.

Module 10

Capstone Project

End-to-end agentic AI system design and implementation project.

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