AutoGPT Workflow Automation

The course AutoGPT Workflow Automation from SpiralTrain teaches you how to build autonomous AI agents using AutoGPT and similar frameworks.

Introduction AutoGPT

The course AutoGPT Workflow Automation begins with an introduction to autonomous AI agents and AutoGPT. Agent frameworks comparison, installation, configuration, goal setting, memory systems, and practical use cases are explored.

Agent Architecture

This module covers the agent loop design including goal decomposition, task planning, reasoning processes, self-reflection, critique mechanisms, decision making, action selection, and feedback loops for continuous improvement.

Tools and Plugins

Here participants learn to work with built-in tools and develop custom tools. Topics include API integrations, web browsing, file operations, code execution, search capabilities, database access, and plugin architecture.

Memory Management

Memory systems are addressed including short-term and long-term memory, vector databases, retrieval strategies, context window management, conversation history, knowledge storage, embeddings, and state persistence for autonomous agents.

Advanced Capabilities

This part focuses on advanced features including multi-agent systems, agent collaboration, human-in-the-loop workflows, constraint management, cost optimization, error handling, guardrails, safety mechanisms, and workflow orchestration.

Production Deployment

The course concludes with production considerations including deployment strategies, environment configuration, API management, monitoring, error recovery, scaling, security best practices, cost management, and testing autonomous agents.

Audience Course AutoGPT Workflow Automation

This course is intended for AI developers, automation engineers, and data scientists who want to build autonomous AI agents using AutoGPT.

Prerequisites Course AutoGPT Workflow Automation

Participants should have a good understanding of Python Programming en AI and LLM concepts. Familiarity with APIs and prompt engineering is beneficial.

Realization Training AutoGPT Workflow Automation

The training combines theoretical instruction with hands-on labs guided by a trainer. Participants build several autonomous agents throughout the course.

AutoGPT Workflow Automation Certificate

After successful completion, participants receive a certificate of participation in AutoGPT Workflow Automation.

Modules

Module 1: Introduction AutoGPT

• AutoGPT Overview
• Autonomous Agents Concepts
• AutoGPT vs ChatGPT
• Agent Frameworks Comparison
• Installation and Setup
• Configuration Basics
• Agent Goals
• Memory Systems
• Use Cases
• Best Practices

Module 2: Agent Architecture

• Agent Loop Design
• Goal Decomposition
• Task Planning
• Reasoning Processes
• Self-Reflection Mechanisms
• Critique and Refinement
• Decision Making
• Action Selection
• Feedback Loops
• Agent Personas

Module 3: Tools and Plugins

• Built-in Tools
• Custom Tool Development
• API Integrations
• Web Browsing
• File Operations
• Code Execution
• Search Capabilities
• Database Access
• Tool Chaining
• Plugin Architecture

Module 4: Memory Management

• Short-Term Memory
• Long-Term Memory
• Vector Databases
• Memory Retrieval
• Context Window Management
• Conversation History
• Knowledge Storage
• Embedding Strategies
• Memory Optimization
• State Persistence

Module 5: Advanced Capabilities

• Multi-Agent Systems
• Agent Collaboration
• Human-in-the-Loop
• Constraint Management
• Cost Optimization
• Error Handling
• Guardrails Implementation
• Safety Mechanisms
• Performance Tuning
• Workflow Orchestration

Module 6: Production Deployment

• Deployment Strategies
• Environment Configuration
• API Key Management
• Monitoring and Logging
• Error Recovery
• Scaling Considerations
• Security Best Practices
• Cost Management
• Testing Autonomous Agents
• Production Checklist