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Course Outline
Introduction to Agentic AI
- Defining agentic AI and its distinction from traditional AI systems
- An overview of reasoning, memory, and goal-oriented architectures
- Key use cases and industry-specific applications
Core Concepts and Design Patterns
- The agent loop: perception, reasoning, and action
- Comparing single-agent and multi-agent systems
- Interaction with environments and tool invocation
Prompt Engineering Fundamentals
- Crafting effective prompts for reasoning and task breakdown
- Leveraging examples, constraints, and role definitions for better control
- Systematic debugging and iterative refinement of prompts
Building Simple Agentic Workflows
- Implementing an agent loop using Python
- Integration with APIs and basic tools
- Management of agent state and memory
Responsible Design and Safety Practices
- Ethical considerations and responsible deployment of agents
- Addressing bias, transparency, and accountability in AI systems
- Implementing access control, data protection, and content safety measures
Hands-on Project: Designing a Responsible Agent
- Defining the problem scope and project objectives
- Developing the prompt structure and control logic
- Testing, refining, and evaluating agent performance
Requirements
- A foundational grasp of AI or machine learning concepts
- Proficiency in Python syntax and scripting
- Practical experience with data handling or API-driven applications
Target Audience
- Data scientists beginning their journey in agentic AI development
- Junior ML engineers exploring 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
