Introduction to AI Tools in Data Management

• Overview of AI Tools and Their Applications in Data Management
  Introduction to browser-based AI tools (ChatGPT, Perplexity, Claude)
  The role of AI in data management and its impact on decision-making
  Examples of AI tools in various industries (healthcare, finance, retail, etc.)

• Introduction to Data Management Systems
  Overview of data management platforms and reporting systems
  How AI tools can complement and integrate with existing data systems

• Hands-On Activity: Exploring AI Tools
  Familiarizing participants with ChatGPT, Perplexity, and Claude interfaces
  Basic exercises to explore AI tools for analyzing and summarizing data

Hands-On Integration with Data Management Systems

• Practical Exercises: Integrating AI with Data Systems
  Using AI tools to query, analyze, and generate insights from real data
  Working with data management and reporting tools to automate data processes
  Enhancing data analysis with AI-generated visualizations

• Automating Report Generation with AI Tools
  Techniques for automating the creation of statistical summaries and reports
  AI-based automation of routine reporting tasks (e.g., weekly, monthly, quarterly reports)
  Creating concise, actionable insights for decision-makers using AI-powered reports

AI-Powered Data Analysis Without Programming

• Simplified Data Cleaning and Organization Using AI
  Using AI tools to clean, process, and organize data without coding
  Automating the identification and removal of duplicates, missing values, and inconsistencies

• Data Analysis with AI
  Leveraging AI for identifying trends, correlations, and patterns in datasets
  Using AI for predictive analysis and forecasting outcomes
  Generating actionable recommendations for business or organizational decision-making

• Hands-On Activity: Analyzing Data with AI
  Participants will use AI tools to analyze their own datasets and generate insights
  Practicing how to interpret AI-generated results and draw conclusions

Creating Reports and Ethical Considerations

• Creating Reports for Stakeholders Using AI
  Summarizing large datasets into concise, easy-to-understand reports
  AI-enhanced data visualizations to support presentations for stakeholders
  Generating narratives and insights tailored for decision-makers

• Ethical Considerations in AI for Data Management
  Ensuring data privacy and security when using AI tools with sensitive data
  Understanding the limitations of AI tools and validating results for accuracy and reliability
  Best practices for ethical AI usage in data management and analysis

• Final Hands-On Exercise: Presenting AI-Generated Insights
  Creating a final report based on a data analysis project
  Using AI tools to generate insights and visualizations for a mock presentation to stakeholders

Conclusion and Certification

• Review and Q&A
  Open discussion on the challenges and benefits of integrating AI into data management
  Troubleshooting and addressing any participant queries

• Certification of Completion
  Participants will receive certificates upon completing the training and submitting a capstone project (if applicable)