Frameworks and Roadmap to Follow for Mastering Agentic AI Systems

Overview

Discover a comprehensive roadmap and framework for mastering Agentic AI systems, exploring autonomous AI that can make decisions, take actions, and adapt without constant human supervision.

Syllabus

• Introduction to Agentic AI Systems
Definition and Characteristics of Agentic AI
Historical Development and Milestones
Importance and Applications of Agentic AI
• Frameworks for Developing Agentic AI
Overview of AI Development Frameworks
Selecting the Right Framework for Your Project
Key Components of Effective AI Frameworks
• Roadmap to Mastering Agentic AI
Initial Steps: Learning the Basics
Intermediate Stage: Building Simple Agentic Models
Advanced Techniques: Developing Autonomous Agents
• Decision-Making in Agentic AI
Fundamentals of AI Decision-Making Processes
Decision Trees and Logic-Based Systems
Probabilistic and Statistical Decision Models
• Autonomous Action Planning
Introduction to Action Planning Theories
Techniques for Action Selection and Execution
Algorithms for Continuous Learning and Adaptation
• Adaptation and Learning Mechanisms
Reinforcement Learning in Agentic Systems
Supervised vs. Unsupervised Learning Methods
Evolutionary and Genetic Algorithms for AI Adaptation
• Ethical Considerations and Monitoring
Ethical Implications of Autonomous Systems
Human Oversight and Control Strategies
Privacy and Security Concerns in Agentic AI
• Case Studies and Applications
Examples of Successful Agentic AI Systems
Industry-specific Applications and Innovations
Analyzing Successes and Failures in Agentic AI Implementation
• Future Trends and Challenges
Emerging Technologies in Agentic AI
Predicting and Preparing for Future Developments
Addressing Global Impacts and Policy Challenges
• Resources for Continued Learning
Recommended Books and Papers
Online Courses and Tutorials
Conferences and Workshops to Attend

Subjects

Computer Science