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Course Outline
Introduction to Agentic AI
- Establishing the definition of agentic AI and its distinction from conventional AI systems
- Exploring reasoning mechanisms, memory structures, and goal-oriented architectural frameworks
- Identifying key use cases and applications across various industries
Core Concepts and Architectural Patterns
- The agent cycle: perceiving inputs, reasoning through options, and executing actions
- Comparing single-agent architectures with multi-agent systems
- Interacting with environments and invoking external tools
Basics of Prompt Engineering
- Crafting effective prompts to facilitate reasoning and task breakdown
- Leveraging examples, constraints, and role assignments for enhanced control
- Systematically debugging and refining prompts for optimal performance
Developing Basic Agentic Workflows
- Constructing an agent loop using Python
- Connecting to APIs and integrating simple utility tools
- Oversight of agent state and memory management
Responsible Design and Safety Protocols
- Navigating ethical considerations and promoting responsible agent usage
- Addressing bias, transparency, and accountability within AI frameworks
- Implementing access controls, data protection measures, and content safety standards
Practical Project: Creating a Responsible Agent
- Defining the problem scope and establishing clear objectives
- Developing the prompt structure and control logic
- Testing, optimizing, and assessing agent behavior
Requirements
- Fundamental comprehension of AI or machine learning principles
- Proficiency with Python syntax and scripting capabilities
- Practical experience with data handling or API-driven applications
Target Audience
- Data scientists initiating their journey into agentic AI development
- Junior ML engineers exploring applied agent architectures
- Technology managers aiming to grasp the design and safety principles underlying agent systems
14 Hours
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
