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Duration 14 hours
Course Outline
Overview of Agentic Artificial Intelligence
- Definition of agentic AI and its distinctions from conventional AI frameworks
- Summary of reasoning capabilities, memory structures, and objective-oriented architectures
- Primary operational applications and sector-specific implementations
Foundational Concepts and Architectural Standards
- The operational agent cycle: observation, cognitive processing, and execution
- Comparative analysis of single-agent and multi-agent configurations
- Interaction protocols with external environments and utility invocation
Prompt Engineering Essentials
- Formulation of structured prompts to enhance logical reasoning and task segmentation
- Utilization of examples, boundary constraints, and role definitions for precise control
- Systematic methods for troubleshooting and iterative prompt refinement
Constructing Basic Agentic Processes
- Execution of an agent loop using Python programming
- Integration of external Application Programming Interfaces (APIs) and auxiliary tools
- Administration of agent state retention and memory management
Responsible Design Protocols and Security Measures
- Ethical guidelines and responsible deployment strategies for autonomous agents
- Addressing bias, ensuring transparency, and establishing accountability mechanisms in AI systems
- Enforcement of access controls, data security, and content integrity standards
Practical Exercise: Architecting a Compliant Agent System
- Establishment of problem parameters and strategic objectives
- Development of prompt structures and regulatory logic
- Testing protocols, optimization iterations, and performance evaluation of agent conduct
Concluding Remarks and Future Recommendations
Requirements
- Fundamental comprehension of AI or machine learning principles
- Proficiency with Python syntax and scripting practices
- Professional experience with data processing or API-centric applications
Target Audience
- Data scientists initiating exploration of agentic AI development
- Junior machine learning engineers investigating applied agent architectures
- Technology administrators seeking insight into agent design and safety frameworks
Testimonials (3)
The trainer is patient and very helpful. He knows the topic well.
CLIFFORD TABARES - Universal Leaf Philippines, Inc.
Course - Agentic AI for Business Automation: Use Cases & Integration
Good mixvof knowledge and practice
Ion Mironescu - Facultatea S.A.I.A.P.M.
Course - Agentic AI for Enterprise Applications
The mix of theory and practice and of high level and low level perspectives
