Best Frameworks to Learn for Building AI Agents and Agentic AI

Overview

Discover the top frameworks for building AI agents and agentic AI applications, with a comprehensive roadmap for learning this cutting-edge technology.

Syllabus

• Introduction to AI Agents and Agentic AI
Overview of AI Agents
Distinction between AI Agents and Agentic AI
Key components of AI agents
• Fundamentals of AI Frameworks
Importance of frameworks in AI development
Criteria for selecting frameworks
• Popular Frameworks for Building AI Agents
PyTorch
Overview and features
Installation and setup
Building simple AI agents with PyTorch
TensorFlow
Overview and features
Installation and setup
Implementing AI agents using TensorFlow
Keras
Overview and features
Integrating with TensorFlow
Developing AI agent applications with Keras
• Reinforcement Learning Frameworks
OpenAI Gym
Setup and environment exploration
Creating agents in OpenAI Gym
Stable Baselines3
Integrating with OpenAI Gym
Developing Reinforcement Learning agents
• Specialized Agentic AI Frameworks
Rasa
Introduction to conversational AI
Building intelligent agents with Rasa
Apache Flink
Real-time data processing for agentic AI
Integrating AI agents with large-scale data
• Advanced Topics
Multi-agent systems with PyMARL
Distributed AI Agent architectures
• Best Practices and Design Patterns
Agent communication and coordination
Scalability considerations for AI agents
• Hands-on Projects
Developing a chatbot with Rasa
Building a reinforcement learning agent with Stable Baselines3
• Future Trends in Agentic AI
The evolution of AI agent frameworks
Emerging trends and technologies
• Conclusion and Further Learning Resources
Recap of key frameworks and skills
Recommended books, courses, and communities for continued learning

Subjects

Computer Science