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Data Science Lab at Politecnico di Milano

Data Science Lab at Politecnico di Milano

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    • Data Management for Large-scale Analytics (PhD Course)

Data Science for Business (Milan)

Motivation

«Many organizations focus on the need for data scientists. But another equally vital role is that of the business translator who can serve as the link analytical talent and practical applications to business questions.»

Target of the course

  • No technicalities or programming skills
  • Aimed at informed decision making on data driven projects
  • Strategic planning, project management,
  • product development, team management,
  • buy or make decisions

Agenda & Material

The course covers two days with a mix of inspirational, theoretical, and workgroup activities. The material refers to the Milan edition where prof. Marco Brambilla and Emanuele Della Valle covered the theoretical [T] parts, Francesco Mapelli and Gianluca Ripa gave the inspirational keynotes [I] and participants performed the workgroup activities [W] with the support of Marco Balduni.

Day 1

  • 9:15 Welcome [slides]
  • 9:30 Self-Definition and Learning Goals [W]
  • 9:45 Keynote: Data Driven Decision and Projects [I] [slides]
  • 10:45 Break
  • 11:00 Self-Positioning [W]
  • 11:15 Principles and motivation of big data and data science [T] [slides]
  • 12:30 Lunch
  • 13:30 Principles of data science project management [T] [slides]
  • 14:30 Business case method [T] [slides]
  • 15:00 Business case – Part 1 [T+W] [photos: working]
  • 15:30 Break
  • 15:45 Business case – Part 2 [W] [photos: goal-posters]

Day 2

  • 9:15  Framing a Data-centric problem [slides]
  • 9:45 Principles and methods for data science from a buiness perspective:
    • ML and Gradient Descent [T] [slides]
    • Product Price Prediction using Regression [T] [slides]
    • Learning to hire fresh graduates using classification [T] [slides]
    • Using Clustering to decide where to open new shops in franchising [T] [slides]
  • 11:00 Break
  • 11:00 Techniques in business case [assignment] [W]
  • 12:30 Lunch
  • 13:15 Risks and challenges in data centric projects [T] [slides]
  • 15:00 Break
  • 15:30 Challenges in business case [W] [photos: data-risks-1,data-risks-2]
  • 16:30 Reporting on business cases [W] [photos: result-1, result-2, result-3, result-4, result-5, result-6]
  • 17:00 Key note by Gianluca Ripa (CEFRIEL) [T] [slides]
  • 17:30 Closing

Recent News

  • PERISCOPE: the EU project on socio-economic and behavioral impacts of the COVID-19 pandemic
  • DATA-LIFE PROGRAM 2020
  • Challenges in Data-Driven Genomic Computing
  • FaST – Fashion Sensing Technology
  • A Tool for Extracting Emerging Knowledge from Social Media
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