AI and Big Data in Business Economics

About This Course:
“AI and Big Data in Business Economics” is a comprehensive 3-week course designed to explore the powerful synergy between advanced AI techniques and economic analysis. In this course, you’ll dive into machine learning, natural language processing (NLP), econometrics, and data visualization, focusing on practical applications in market behavior modeling, financial forecasting, and policy simulation.

Throughout this course, you’ll work with real-world business and economic datasets, using tools like Python (pandas, scikit-learn), Power BI, Tableau, and machine learning frameworks. By the end, you will be able to uncover trends, derive actionable insights, and predict economic outcomes that shape business strategies and influence economic policy.

Course Aim:
The goal is to empower business professionals, economists, analysts, and researchers with the tools and frameworks necessary to apply Artificial Intelligence and Big Data analytics to solve complex economic and business problems. This course will enhance participants’ ability to drive intelligent strategy, forecasting, and informed policy-making in business economics.

Course Objectives:

• Develop cross-functional expertise in economics, AI, and big data analytics.

• Learn to create data-driven, AI-powered economic models and design effective policies.

• Gain hands-on experience with tools like Python, Power BI, Tableau, and ML libraries.

• Foster responsible and transparent data use in decision-making.

• Prepare participants to lead innovation in economic intelligence and strategy.

Course Structure:

📌 Module 1: AI & Big Data Foundations for Economic Insights
Theme: Exploring Data-Driven Economic Intelligence

• Transitioning from traditional economic models to AI-based forecasting.

• Sourcing and integrating real-time economic/business datasets (World Bank, IMF, UNCTAD, Statista APIs).

• Understanding data pipelines, feature engineering, and data transformation.

• Overview of essential tools: Python, R, Jupyter, Pandas, Power BI.

Hands-On Activities:

• Live coding session: Cleaning and transforming real-world economic data.

• Practical exercise: Economic indicator mapping using Python & Excel.

• Visual analytics using Power BI/Tableau for trade, inflation, and fiscal trends.

📌 Module 2: Advanced AI for Forecasting, Strategy & Market Intelligence
Theme: Building Predictive and Prescriptive Economic Models

• Developing forecasting models (ARIMA, LSTM, Prophet) for GDP, inflation, and FDI flows.

• AI-based classification for business risk and consumer behavior segmentation.

• Introduction to NLP for policy document and sentiment analysis.

• Applications of Transformer models (BERT) for analyzing economic surveys and budgets.

Hands-On Activities:

• Model training lab: Build & validate economic forecasting models in Python.

• Predicting inflation rates using LSTM and Prophet with IMF datasets.

• Sentiment analysis: Budget speech classification using NLP pipelines.

📌 Module 3: Strategic AI Systems, Dashboards & Ethical Economics
Theme: From Insight to Implementation in Business & Policy

• Building scalable AI pipelines for business economics using cloud tools (Azure, Colab, MLFlow).

• Integrating AI into business intelligence dashboards for CFOs and policy units.

• Principles of explainable AI, fairness, and accountability in economic applications.

• Overview of global regulations: OECD AI Principles, RBI AI Guidelines, EU AI Act.

Hands-On Activities:

• End-to-end build: Real-time economic dashboard using Streamlit/Power BI.

• SHAP & LIME lab: Interpreting AI models in economic decision-making.

Who Should Enrol?

• Business economists and economic analysts.

• Finance and investment professionals.

• Data scientists in corporate strategy or consulting.

• Policy researchers and academic scholars.

• UG/PG/PhD students in economics, business analytics, or data science.