Objective

This retail project will allow the participant to gain a deep understanding of how machine learning and artificial intelligence is capitalized on in the retail space and have a comprehensive overview of the various use cases possible with different kinds of retail data. Some of the use cases are as follows:

  • Predicting customer satisfaction 
  • Identifying product categories prone to customer dissatisfaction, under quality control
  • Optimizing delivery performance and estimation
  • Feature engineering: Generating rich features from the given dataset
  • Customer Lifetime Value (CLV)
  • Demand Forecasting: Predicting future sales volume

Methodology

Participants will use a publicly available retail database for the project. Various machine learning algorithms as per the use case will be covered.

Benefits

This project will help students understand machine learning algorithms and gain valuable insights into the workings of the retail industry.

Duration: 3-6 Months (Online – Offline, Instructor based)