Become an Agentblazer Champion

Overview

Explore core AI concepts and build a basic agent for key tasks.

Syllabus

• Introduction to Artificial Intelligence
Definition and History of AI
Key AI Techniques and Applications
• Core AI Concepts
Machine Learning Basics
Supervised, Unsupervised, and Reinforcement Learning
Neural Networks and Deep Learning Introduction
• Intelligent Agents
Definition and Purpose of Agents in AI
Types of Agents: Reactive, Deliberative, Hybrid
Environments and Agent Perceptions
• Planning and Decision Making
Problem-Solving Techniques
Search Algorithms (BFS, DFS, A*)
Introduction to Game Theory and Strategic Planning
• Building an AI Agent
Setting Objectives and Defining Tasks
Agent Architectures and Frameworks
Development tools and programming basics
• Specific Agent Tasks
Navigation and Pathfinding
Resource Management
Interaction with Environment and Feedback Loops
• Testing and Evaluation
Metrics for Assessing Agent Performance
Iterative Improvement Processes
• Advanced Topics and Future Directions
Ethical Considerations in AI
Future of AI Agents and Emerging Technologies
• Hands-On Project: Building Your Basic Agent
Project Requirements and Constraints
Implementation and Testing Process
Final Presentation and Feedback Session

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Subjects

Business