Module 1: Foundations of AI Agents
Introduction to AI Agents: Core principles, architecture, and operational mechanisms
Prompt Engineering: Advanced techniques for optimizing AI model interactions
Applications and Frameworks: Analysis of prevalent use cases and solution design methodologies
Development Environment Setup: Configuration of essential tools and platforms for AI agent development
Module 2: Designing a Customer Support AI Chatbot
Chatbot Development: Constructing an intelligent chatbot using Zapier, n8n, Python, and large language models (LLMs)
Core Functionality: Implementing natural language processing for effective customer query resolution
Practical Implementation: Step-by-step guidance on building and testing a responsive chatbot system
Module 3: Building a Marketing Analytics Agent
Automated Analytics System: Developing a robust marketing analytics engine
Data Acquisition and Analysis: Fetching real-time news data and performing sentiment analysis
Automated Reporting: Summarizing insights and automating email-based report distribution
Integration Tools: Leveraging Zapier, n8n, and Python for seamless workflow automation
Module 4: Advanced AI Agent Development
Sophisticated AI Solutions: Utilizing LangChain, Zapier, and Python to create scalable and resilient AI agents
Advanced Methodologies: Enhancing agent performance through complex workflows and integrations
Scalable Design: Architecting agents to support diverse and evolving business requirements
Module 5: Production Deployment Strategies
Deployment Fundamentals: Key considerations for deploying AI agents in production environments
Cloud-Based Deployment: Configuring and deploying solutions on cloud platforms, such as Microsoft Azure
Operational Best Practices: Ensuring reliability, scalability, and security in live deployments
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