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Duration 14 hours
Course Outline
Introduction to Agentic AI
- Establishing the definition of agentic AI and its distinctions from conventional AI systems
- Examining the roles of reasoning, memory, and goal-oriented architectural structures
- Exploring significant use cases and sector-specific applications
Foundational Principles and Design Methodologies
- The agent cycle: analyzing perception, reasoning, and execution phases
- Comparative analysis of single-agent versus multi-agent system architectures
- Mechanisms for environmental interaction and tool activation
Essentials of Prompt Engineering
- Structuring high-impact prompts to facilitate reasoning and task breakdown
- Leveraging examples, constraints, and role-based instructions for enhanced system control
- Systematic approaches to debugging and refining prompt iterations
Constructing Basic Agentic Workflows
- Programming the agent loop using Python
- Connecting agents to external APIs and basic utility tools
- Overseeing agent state management and memory retention
Ethical Design and Safety Protocols
- Evaluating ethical implications and responsible deployment of agents
- Addressing bias, ensuring transparency, and maintaining accountability in AI frameworks
- Enforcing access controls, data security measures, and content safety standards
Practical Exercise: Engineering a Responsible Agent
- Defining the project scope and primary objectives
- Creating the necessary prompts and control logic structures
- Conducting tests, refining functionality, and assessing agent performance
Requirements
- Foundational knowledge of AI or machine learning principles
- Working familiarity with Python syntax and scripting conventions
- Practical experience handling data or interacting with API-driven applications
Target Audience
- Data scientists initiating their journey into agentic AI development
- Junior ML engineers investigating applied agent architectural models
- Technology leaders aiming to grasp the principles of agent design and operational safety
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
