The Executive Development Programme in Business Analytics and Big Data curriculum is methodically organized to build progressive expertise in data analysis and big data technologies. The program begins with foundational concepts in the "Introduction to Business Analytics" module, establishing the various types of analytics and their business applications, while introducing machine learning as a key tool for data-driven decision making. The "Introduction to Python" module provides the technical foundation necessary for implementing analytics solutions, covering everything from basic syntax to advanced object-oriented programming concepts. Moving from theory to application, the curriculum advances to "Descriptive and Visual Exploratory Analytics" and "Foundations of Inferential Analytics," equipping participants with the skills to summarize, visualize, and draw preliminary conclusions from data. The program then shifts to predictive modeling through the "Business Context: Prediction" and "Machine Learning Context: Regression" modules, introducing various regression techniques and diagnostic tools for forecasting business outcomes. The classification section follows with detailed coverage of techniques like logistic regression, decision trees, and support vector machines, along with practical methods for evaluating model performance through confusion matrices and cost-benefit analysis. Advanced machine learning methods expand participants' analytical toolkit with ensemble approaches like boosting and bagging. The "Business Context: Segmentation" and "Machine Learning Context: Clustering" modules teach participants to identify natural groupings in data using various clustering algorithms, essential for market segmentation and customer profiling. The curriculum then addresses unstructured data through text analytics modules, covering sentiment analysis and topic modeling, increasingly important skills in the age of social media and digital communication. The big data portion of the program introduces participants to distributed computing concepts, the Hadoop ecosystem, and practical implementation of big data solutions on both local machines and cloud platforms like AWS. Finally, the program covers specialized applications including recommender systems and market basket analysis, before culminating in capstone projects that allow participants to demonstrate their comprehensive learning. This thoughtfully sequenced curriculum ensures participants develop both theoretical understanding and practical implementation skills across the complete spectrum of business analytics and big data technologies.