1. Introduction to Business Intelligence in Agriculture - Overview of data-driven decision-making in agribusiness - Introduction to business intelligence tools and their relevance in the agricultural market 2. Excel for Advanced Data Analysis - Advanced functions in Excel for data processing - Practical exercises using Excel for agricultural market data analysis - Introduction to AI-enhanced features in Excel 3. Data Visualization Techniques - Creating charts, graphs, and dashboards for effective data presentation - Customizing visualizations to reflect agricultural business trends 4. AI in Agricultural Business - Overview of AI applications in agribusiness - Using AI tools in Excel to enhance data analysis - Predictive modeling and trend forecasting using AI 5. Case Studies in Agricultural Data Analysis - Analysis of real-world agricultural market data - Identifying key insights and making data-driven business decisions - Discussion of successful AI applications in agribusiness 6. Big Data Analysis for Agribusiness - Understanding the role of big data in agriculture - Techniques for analyzing large datasets relevant to agricultural business - Applying AI to extract actionable insights from complex data sets 7. Implementing Business Intelligence Strategies - Developing data-driven strategies for agricultural businesses - Case study-based strategy development using Excel and AI tools 8. Course Project: Developing an Agribusiness Intelligence Plan - Students will apply learned concepts to create a comprehensive business intelligence plan using Excel and AI tools - Presentation and discussion of project findings Learning Outcomes: - Master advanced Excel functions and AI tools for agribusiness data analysis - Develop data visualization skills to present agricultural market insights - Apply AI for predictive modeling in agricultural business contexts - Create data-driven strategies for optimizing agribusiness operations and decision-making