Applied Data Science Project (ADSP 02TXXWS - 8 CFU)

2025-2026 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

Lectures (26 hours)

Building an artificial intelligence application (1.5h)
Introduction to project pillars: management, design, development and communication (1.5h)
Model and Data-centric projects (1.5h)
Foundation models (1.5)
Retrieval Augumented Generation (1.5h)
Artificial intelligence ethics (1.5h)
Impact of a project and SGDs (1.5h)
Project tools (14h)
Management: GANTT, Work breakdown structure, work packages and tasks, milestone
Design: User personas, stakeholder map, functional requirements
Development:
Foundation models: Large language models and vision language models
Domain adaptation and downstream tasks
Retrieval Augumented Generation implementation
Version control and testing
Communication: Presentation, Technical Paper, Deliverable
Success stories of past projects (1.5h)

Laboratory activities (54h)

Project proposals (1.5h)
User-centred application (3h)
Stakeholder maps and user personas
User journey
Use of SDKs and REST APIs of commercial neural models with prompt engineering (6h)
Use of Ollama with open source models (3h)
Development of the team project (40.5)

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
Proposal for a Regulation laying down harmonised rules on artificial intelligence, European Commission, 2021

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 (teaching assistant)
Federico D’Asaro (teaching assistant)
Luca Barco (teaching assistant)

Previous editions

The entire course material is shared with license CC BY 4.0

Contacts

For any question, feel you free to mail giuseppe.rizzo@polito.it