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Duration 14 hours
Course Outline
Introduction to Agentic AI
- Defining agentic AI and distinguishing it from conventional AI systems
- An overview of reasoning mechanisms, memory structures, and goal-oriented architectures
- Exploring key use cases and real-world industry applications
Core Principles and Architectural Patterns
- The agent cycle: encompassing perception, reasoning, and action
- Comparing single-agent frameworks with multi-agent ecosystems
- Interacting with environments and invoking external tools
Essentials of Prompt Engineering
- Crafting effective prompts for logical reasoning and task breakdown
- Leveraging examples, constraints, and role definitions for enhanced control
- Systematically debugging and iterating on prompts for improvement
Creating Basic Agentic Workflows
- Building an agent loop using Python
- Connecting with APIs and integrating simple utility tools
- Handling agent state management and memory persistence
Responsible Design and Safety Protocols
- Ethical implications and best practices for responsible agent deployment
- Addressing bias, ensuring transparency, and maintaining accountability in AI
- Implementing access controls, data privacy safeguards, and content safety measures
Practical Project: Developing a Responsible Agent
- Establishing the problem scope and defining clear objectives
- Constructing the prompting strategy and control logic
- Testing, refining, and assessing the agent's performance and behavior
Requirements
- A solid grasp of foundational AI or machine learning concepts
- Proficiency in Python syntax and basic scripting
- Practical experience interacting with data structures or API-driven applications
Target Audience
- Data scientists beginning their journey in agentic AI development
- Junior machine learning engineers exploring applied agent architectures
- Technology managers aiming to grasp the intricacies of agent design and safety protocols
Testimonials (3)
Strong confirmation that current LLMs are deployable for customer projects when the proper setup is in place.
Oliver Fromm
Course - Agentic AI for Enterprise Applications
Machine Translated
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
The mix of theory and practice and of high level and low level perspectives
