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Duration 14 hours (2 days)
Course Outline
Introduction to Agentic AI
- Defining agentic AI and its distinction from traditional AI systems
- Examining reasoning processes, memory structures, and goal-oriented architectures
- Reviewing primary use cases and industrial applications
Foundational Concepts and Architectural Patterns
- The agent cycle: perception, reasoning, and execution
- Comparing single-agent and multi-agent configurations
- Interactions with environments and calling external tools
Essentials of Prompt Engineering
- Crafting prompts that facilitate reasoning and task breakdown
- Leveraging examples, constraints, and role assignments for enhanced control
- Systematically debugging and refining prompt performance
Constructing Basic Agentic Workflows
- Building an agent loop using Python
- Connecting agents with APIs and basic utility tools
- Oversight of agent state and memory management
Ethical Design and Safety Protocols
- Addressing ethical implications and the responsible deployment of agents
- Managing bias, ensuring transparency, and maintaining accountability in AI
- Implementing access controls, data security, and content safety measures
Practical Project: Creating an Ethical Agent
- Establishing the problem scope and project goals
- Formulating prompt structures and control mechanisms
- Testing, optimizing, and assessing agent performance
Requirements
- A foundational grasp of artificial intelligence or machine learning principles
- Working knowledge of Python syntax and scripting conventions
- Prior experience with data manipulation or API-centric applications
Target Audience
- Data scientists beginning their journey into agentic AI development
- Junior machine learning engineers investigating practical agent architectures
- Tech leaders looking to comprehend agent design methodologies and safety standards
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
