Predictive Analytics for Demand Forecasting and Planning

This programme aims to introduce participants to the importance of forecasting in demand planning with a special focus on latest analytics and machine learning tools such as regression, decision trees, random forest and boosting algorithms. The program is designed keeping in mind the various techno-managerial aspects that need to be addressed by the participants. IIM Mumbai faculty have been working on different domains of applications of statistics, operations research, artificial intelligence and machine learning, and are actively involved in consulting and applied research projects in the area of operations and supply chain management. The program is designed as the effective blend for application orientation with plenty of hand-on case exercises. MS Excel and Python programming will be used for the sessions. Python software shall be used.

Pedagogy:

  • Web-based Lectures/ Case Study
  • Demonstration
  • Hands-On experience with coding in Python
  • Group projects

 

Prof.Debabrata Das (Program Chair)

Prof. Priyanka Verma

Prof.Priyanka Verma (Program Co-Chair)

Prof. Sushmita N. (Program Co-Chair)

 

 

 

Upon successful completion of the program, participants

  • will be familiarized with the concepts of demand forecasting and planning.
  • will be able to learn and apply various forecasting models with a special focus on latest analytics and machine learning tools such as regression, decision trees, random forest and boosting algorithms.
  • will learn coding and solving the forecasting problems in Python.

 

Day Topic
Day 1
  • Introduction to Forecasting
  • Overview of Data Analytics for Forecasting
  • Forecasting Patterns
  • Forecasting Methods and Comparisons (SMA, Exponential Smoothing, Holt’s Model, Seasonality Models)
  • Forecasting Errors
  • Hands-on Case Example on Forecasting
Day 2
  • Linear Regression – Simple & Multiple
  • Linear Regression – Hands-On Exercise with Case Study
  • Decision Trees Algorithm
  • Decision Trees Algorithm – Hands-on Exercise with Case Study
Day 3
  • Random Forest Algorithm 
  • Random Forest Algorithm- Hands-On Exercise with Case Study
  • Gradient Boosting Methods
  • XGBoost and ADA Boost Algorithms
  • Hands on Exercise on Boosting Algorithms with Case Study

This training program is designed for web-based learning with hands-on exercises for executives in managerial positions in any organization.

 

  1. Registration fees include the following:

    For all the participants:

    • Online sessions
    • Online study material
    • Certificate for course completion

  2. Refund policy

    Fees once paid can be adjusted for 1 financial year against future nominations only. In case a course is canceled on account of inadequate participation or any other unforeseeable reasons, the participants will be informed of the cancellation by e-mail or Fax and the fee will be refunded. IIM Mumbai will not be liable for any other expenses incurred by the company or the participant. Any transaction fee will not be refunded.

  3. Individual Registration

    If you wish to register & make payment, please click here Register

  4. Company-sponsored / Bulk Registration:

    • In the case of company-sponsored candidates, please share the nomination list and GST details to program@iimmumbai.ac.in for invoice generation.

      Download the INVOICE DETAILS FORM

    • Note: Discount is applicable for 5 or more participants from same organization against invoice.

Course Details

Mode Online / Virtual
Duration 3 Days
Programme Dates Jan 18, 2025 to Jan 25, 2025 (Saturday & Sunday 10.00 am to 5.00pm )
Program Chair Prof. Debabrata Das
Program Co-Chair Prof. Priyanka Verma and Prof. Sushmita Narayana

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