Course Duration

2 Days

Audience

Employees of federal, state and local governments; and businesses working with the government.

Prerequisites

No prerequisites required.

Course Description

This two-day, hands-on course provides practical experience with cutting-edge AI systems to help professionals transform the way they work. This course focuses on AutoGPT and similar AI agent frameworks that build upon large language models such as GPT-4 and beyond, enabling autonomous task execution, workflow automation, and business process optimization. While ChatGPT focuses primarily on interactive dialogue, AutoGPT and related systems can perform multi-step operations, integrate with business tools, and make intelligent decisions with minimal human supervision. Participants will explore these technologies through guided examples, hands-on labs, and use cases covering text generation, data analysis, process automation, and decision support.

Learning Objectives

Create high-quality text and content for emails, reports, marketing materials, and other business communications using AI agents, copilots, and automation frameworks such as AutoGPT.
Analyze and visualize data using AI-powered tools to extract insights, identify trends, and support informed, data-driven decisions.
Automate and streamline workflows by integrating AI systems with existing business tools and platforms to boost productivity and reduce repetitive tasks.
Improve collaboration and communication by applying AI-assisted tools for document review, project management, and team knowledge sharing.
Adapt and customize AI models or agents to meet specific organizational needs, ensuring responsible use and effective deployment across business functions.
Apply best practices for ethical, secure, and optimized AI use, including troubleshooting, performance tuning, and maintaining high-quality outcomes in everyday workflows.

Course Outline

1.) Introduction to AI Agents and AutoGPT

Overview of Artificial General Intelligence (AGI) and AI Agents such as AutoGPT
Common business use cases for AI Agents and Copilots
Architecture and core components of AI automation systems
Data privacy and security considerations
Lab: Exploring AI Agents

2.) AI Agents for Text Generation

Generating text for emails, reports, and marketing materials
Text summarization and information extraction
Optimizing text generation quality and controlling output
Ethics and responsible use of text generation
Formulating prompts and instructions
Configuring model parameters (temperature, max tokens, etc.)
Handling long documents and generating coherent text
Fine-tuning and customizing models for specific tasks
Lab: Text Generation and Summarization

3.) AI Agents for Data Analysis

Analyzing datasets and generating insights with AI automation tools
Data visualization and chart creation
Time series forecasting
Integrating AI systems with Excel, Google Sheets, and other platforms
Lab: Data Analysis and Visualization

4.) AI Agents for Automating Business Processes

Streamlining repetitive tasks with AI automation tools
Implementing basic chatbots and customer support systems
Workflow automation and integration with third-party tools
Monitoring and managing automation performance
Lab: Process Automation, creating a workflow automation

5.) AI Agents for Decision Support

Natural language processing for decision support
Sentiment analysis and customer feedback
Risk assessment and fraud detection
Market research and trend analysis
Lab: Use AI tools to analyze customer feedback and make data-driven decisions

6.) Customizing AI Agents

Fine-tuning AI models for specific business needs
Training new models on your data
Evaluating and improving model performance
Deploying custom AI agents within your organization
Lab: Customizing and Training Models

7.) AI Agents for Collaboration and Teamwork

Collaborative editing and document review with AI tools
Enhancing communication and productivity in remote teams
AI-assisted project management and planning
Managing and organizing shared knowledge using AI systems
Lab: Collaboration and Teamwork

8.) Best Practices and Troubleshooting

Ensuring high-quality output and avoiding common pitfalls
Monitoring usage and managing resources effectively
Scaling AI automation systems for larger organizations
Staying up to date with AI agent and AutoGPT community developments

AI Agents in Action: Generative Intelligence for Everyday Business Use