Harnessing Data Mining and Generative AI for Strategic Decision-Making

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Day 1: Introduction to Data Mining

Overview of the data mining process

Introduction to Orange software

Data exploration in Orange

Prediction and classification basics

a) Logistic Regression b)Decision Trees

Hands-on: Building a simple classification model using Orange.

Day 2: Foundation of Generative AI

Neural networks and basics of deep learning

Basics of text mining

Hands-on: Using Orange for understanding traditional ML models and NLP.

Day 3: Integrating Data Mining and Generative AI

Introduction to generative AI

a) Overview of foundation models (GPT, DALL-E, etc.) b) Applications of generative AI in business

Prompt engineering basics

Hands-on exercises: Creating business-focused insights using various generative AI tools

Ethical considerations in AI adoption

On successful completion of the course, participants should be able to: Understand what business analytics entails and how businesses include data mining and generative AI as part of their strategy.

1. Gain a high-level understanding of supervised learning, unsupervised learning, and generative AI models.

2. Learn best practices in data mining and generative AI and how these technologies can be applied in practical business scenarios.

3. Gain hands-on experience with Orange and generative AI tools for business applications.

4. Develop managerial insights into the promises and pitfalls of data mining and generative AI methodologies.