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Course Outline
Foundations of Agentic AI
- Defining agentic AI and distinguishing it from conventional AI systems
- An overview of reasoning mechanisms, memory structures, and goal-oriented architectures
- Key use cases and their applications across various industries
Essential Concepts and Architectural Patterns
- The agent loop: encompassing perception, reasoning, and action
- Comparing single-agent versus multi-agent configurations
- Interacting with environments and invoking external tools
Basics of Prompt Engineering
- Crafting effective prompts to support reasoning and task breakdown
- Leveraging examples, constraints, and role definitions for enhanced control
- Systematically debugging and refining prompts
Developing Basic Agentic Workflows
- Creating an agent loop implementation in Python
- Connecting agents to APIs and simple utility tools
- Handling agent state and memory management
Ethical Design and Safety Protocols
- Examining ethical implications and responsible deployment of agents
- Addressing bias, transparency, and accountability within AI systems
- Implementing access control, data security, and content safety measures
Practical Project: Engineering a Responsible Agent
- Establishing the problem scope and project goals
- Creating the prompt strategy and control logic
- Testing, tuning, and assessing agent performance
Requirements
- A foundational grasp of artificial intelligence or machine learning principles
- Comfort with Python syntax and basic scripting
- Practical experience handling data or working with API-driven applications
Target Audience
- Data scientists beginning their exploration of agentic AI development
- Junior machine learning engineers looking to apply agent-based architectures
- Tech leaders aiming to comprehend agent design principles 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
