Applied Data Science Project (ADSP 01TXXSM)

2021-2022 1st Semester

The course is offered in the first semester of the 2nd year at Politecnico di Torino, Data Science and Engineering. The course is in English.

The course covers the main pillars of executing a successful data science project ranging from the computational and management aspects to the communication one. The goal of this course is to let students face, for the first time, a long running project and learn how to manage all project steps (problem specification, task assignment, design and implementation of the solution, testing, milestones management, writing of intermediate and final reports, result communication). Laboratory activities will expose students with first-hand experience in projects that use massively data science methodologies in collaboration with companies and applied research institutes with an international breadth.

Topics

• Introduction [slides]
• Model and Data-centric projects [slides]
• Foundation models [slides]
• Sustainable development goals and data science examples [slides]
• Data Science project pillars [slides]
  • Design
  • Develop
  • Manage
  • Communicate
• 10 Practical tips [slides]
• Data Science project tools
  • Project design tools
    • Persona canvas and functional diagram [slides]
    • Agile [slides]
    • Scrum [slides] and [example]
  • Project management tools [slides]
  • Project development tools
    • Program development [slides] and [example]
    • Version control [slides]
    • Internal dev communication [slides]
  • Project communication tools
    • Presentation [slides]
    • Paper [slides]
    • Deliverable [slides]
• Success stories [slides]
• Project proposals

Some Past Projects

• Privacy Preserving Health Insurance Cross-sell Prediction
  • [proposal] by Accenture Labs France
  • [presentation] and [paper]
• Job Skill Recommendation
  • [proposal] by INDA
  • [presentation] and [paper]

Expected Learning Outcomes

• Knowledge of first-hand computational tools to address Data Science projects
• Knowledge of management strategies and tools
• Knowledge of communication tools and skills
• Knowledge of the best-practices for value-oriented project setup and execution
• Hands on experience with a real data science project offered by companies or research institutes

Pre-requirements

• Statistics
• Data mining
• Machine learning and Deep learning
• Python language
• Relational, NOSQL, graph databases

Course structure

The course includes practices on the lecture topics, laboratory sessions for the execution of the projects, and meetups with the company key resources (project managers and project leaders) to successfully execute the assigned projects.

Team

Giuseppe Rizzo (owner of the course, prof), Marco Torchiano (prof), Alberto Benincasa, Luca Colomba, Salvatore Greco (teaching assistants)

Share material

The entire course material is shared with license CC BY 4.0

Contacts

For any question, feel you free to drop an email to giuseppe.rizzo@polito.it