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Course Outline
Introduction to Agentic AI
- Defining agentic AI and its distinction from conventional AI systems
- An overview of reasoning, memory, and goal-oriented architectures
- Notable use cases and sector-specific applications
Core Concepts and Design Patterns
- The agent cycle: sensing, reasoning, and execution
- Differentiating single-agent and multi-agent configurations
- Interacting with environments and invoking external tools
Prompt Engineering Fundamentals
- Crafting prompts that facilitate reasoning and task breakdown
- Leveraging examples, constraints, and role definitions for enhanced control
- Systematic debugging and iterative refinement of prompts
Building Simple Agentic Workflows
- Implementing the agent loop using Python
- Connecting with APIs and lightweight tools
- Overseeing agent state and memory management
Responsible Design and Safety Practices
- Ethical frameworks for the responsible use of autonomous agents
- Addressing bias, ensuring transparency, and establishing accountability
- Safeguarding access, protecting data, and maintaining content integrity
Practical Project: Creating a Responsible Agent
- Establishing the problem scope and defining objectives
- Developing the prompt structure and control logic
- Testing, optimising, and assessing agent performance
Requirements
- A foundational grasp of AI or machine learning concepts
- Proficiency in Python syntax and scripting
- Hands-on experience with data handling or API-driven applications
Target Audience
- Data scientists beginning their journey in agentic AI development
- Junior ML engineers investigating practical agent architectures
- Technology leaders seeking clarity on agent design and safety standards
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
