Students will collaborate with your business in groups of three to seven to determine your needs and offer practical solutions based on their in-depth investigation and analysis.

Project activities might include but are not limited to:

• Analyze a complex project using business analytics.
• Gain insights for decision-makers by utilizing data mining and data visualization approaches.
• Make predictions using methods for descriptive and predictive analysis.
• Be able to produce or comprehend primary data to answer a question, as well as recognize appropriate secondary data sources for doing so.
• Clearly communicate outcomes to an outside audience and be able to provide a summary of those results.
• Examine a challenging assignment using business analytics
• possess self-discipline, leadership qualities, outstanding communication skills, a strong work ethic, and the capacity to work autonomously.
• Keep team members informed on any product management knowledge
• Use the proper statistical modeling approaches, such as k-nearest neighbors, random forests, logistic regression, decision trees, naive Bayes' classifier, time series analysis, neural nets, and boosted trees.
• Give the mathematical formula used by the statistical model to forecast the probability of success.
• Recommendations that cover the commercial aspects of model deployment
• Analysis of the budget to examine a wide range of data, assess costs and benefits, and resolve challenging issues