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Course Outline
Getting Started with Agentic AI
- Defining agentic AI and examining its distinction from traditional AI systems
- Surveying reasoning, memory, and goal-oriented architectures
- Exploring key use cases and their application across industries
Fundamental Concepts and Design Patterns
- Understanding the agent cycle: perception, reasoning, and action
- Comparing single-agent and multi-agent system architectures
- Managing interactions with environments and invoking tools
Essentials of Prompt Engineering
- Crafting effective prompts for complex reasoning and task breakdown
- Leveraging examples, constraints, and role definitions for enhanced control
- Systematically debugging and refining prompts for optimal performance
Creating Basic Agentic Workflows
- Building an agent loop using Python
- Connecting agents with APIs and simple utility tools
- Handling agent state management and memory retention
Responsible Design and Safety Standards
- Addressing ethical implications and the responsible deployment of agents
- Managing bias, ensuring transparency, and establishing accountability in AI
- Implementing access controls, data protection measures, and content safety checks
Practical Project: Crafting a Responsible Agent
- Establishing the problem scope and defining clear objectives
- Developing the necessary prompts and control logic
- Testing, refining, and assessing the agent’s behavior and output
Requirements
- A foundational grasp of AI or machine learning principles
- Proficiency in Python syntax and scripting
- Practical experience handling data or working with API-based applications
Target Audience
- Data scientists entering the field of agentic AI development
- Junior ML engineers investigating applied agent architectures
- Technology managers looking to comprehend agent design and safety principles
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
