Applied Data Science Project (ADSP 01TXXSM)

2022-2023 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 main objective of the course is to carry on the development of an artificial intelligence solution utilizing a data science approach. The topics of the course range from the design, development and management aspects to the communication of the project leading to the finalization of the solution. 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 massively use data science methodologies in collaboration with companies and applied research institutes with an international breadth.

Topics

• Introduction: building an artificial intelligence solution with a data science approach [slides]
• Pillars [slides]
  • Design: life and human centered design
  • Develop: foundation models and domain-adaptation
  • Manage: GANTT e work breakdown structure
  • Communicate: paper, deliverable and slides
• Model and Data-centric projects [slides]
• Foundation Models [slides]
• Practical tips [slides]
• Impact of a project and SGDs [slides]
• Tools
  • Design:
    • Human centered-design [slides], Stakeholder maps [slides]
    • Personas [slides], HCD Journey [slides]
    • From user research to solution definition [slides]
  • Manage: WBS, Work packages and tasks, Milestones, GANTT [slides]
  • Develop
    • Colaboratory [slides] [notebook]
    • Foundation models: hub and examples [slides] [notebook]
    • Version control [slides]
    • Team communication [slides]
  • Communicate: slides [slides], paper and deliverable [slides]
• Success stories [slides]
• Project proposals [slides]

Expected Learning Outcomes

• Knowledge of first-hand computational tools to address data science projects
• Knowledge of the design best practices and tools
• Knowledge of management strategies and tools
• Knowledge of communication tools and skills
• Knowledge of the solution impact
• Hands on experience with a real data science project offered by companies and research institutes

Pre-requirements

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

Course structure

The course is structured in three folds:

• Introduction to the concepts to perform a project
• Introduction to the tools to put in place the concepts
• 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.

Reading materials

Copies of the slides used during the lectures will be made available. All teaching material is downloadable from both the teaching portal and this website.

Reference books:

• Machine Learning Yearning, by Andrew Ng
• Data Science from Scratch, Joel Grus
• Harvard Business Review Project Management Handbook: How to Launch, Lead, and Sponsor Successful Projects, by Antonio Nieto-Rodriguez
• Oxford Guide to Effective Writing and Speaking: How to Communicate Clearly, by John Seely
• The Design of Everyday Things: Revised and Expanded Edition, by Donald Norman
• Noessel C. Designing Agentive Technology. AI That Works for People. Rosenfeld, 2013

Teaching Team

Giuseppe Rizzo (owner of the course, prof of AI and Data Science tools), Antonella Frisiello (prof of Service Design and UX), Alessandro Fiori, Edoardo Arnaudo, Bartolomeo Vacchetti (teaching assistants)

Previous editions

• 2021-2022 ADSP 1st Semester

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