Instructors:

• Anna Monreale
  • KDDLab, Università di Pisa
  • anna [dot] monreale [at] unipi [dot] it
• Lorenzo Mannocci
  • KDDLab, Università di Pisa
  • lorenzo [dot] mannocci [at] di [dot] unipi [dot] it

[22-10-2026] Project Deadlines - Mid-projects

Dear all,

The final deadline for the project has been set to 4 January 2027. Please note that this deadline is final and cannot be extended under any circumstances. However, you are welcome to submit your project earlier.

The intermediate project presentations will take place on 23 and 24 November 2026, during the regular lecture hours. Each group will have 6 minutes for the presentation and 3 minutes for questions. You are required to prepare a PowerPoint presentation to illustrate the current progress of your project.

To register for the presentations, please use the shared Google Sheet. Each group must select one available time slot on either 23 or 24 November and enter its group information in the corresponding row. Slots are assigned on a first-come, first-served basis, so please choose a slot that has not already been taken by another group. Only one member per group needs to complete the registration.

The registration deadline is 6 November 2026.

The presentations will be public, meaning that other students are welcome to attend. Please remember that these presentations are not part of the exam evaluation. Their purpose is to provide an opportunity to discuss your progress, receive feedback, and identify potential issues before the final submission.

Best regards, Lorenzo

[01-10-2026] First Part of the Project + Q&A Google Sheet

Hi everyone,

We have uploaded the first part of the project on Didawiki. For your convenience, I am also attaching the PDF here on Teams, so you can access it directly.

We are also sharing a Google Sheet where you can post questions about the project:

🔗 Google Sheet for project questions: https://docs.google.com/spreadsheets/d/1rYpTG-dHj8My3k-7kJGb94EiV_B-gNvWNN6EeCN8Bdw/edit?usp=sharing

Please use the sheet to add your questions, so that the answers can be shared with everyone. Keep in mind that if a question concerns aspects that are part of the project evaluation, we may not be able to provide a direct answer or specific guidance, as determining the appropriate approach may itself be part of the task.

Lorenzo

[28-09-2026] Project Presentation - October 1

Hi everyone, On Thursday, October 1, we will present the exam project and introduce the first task. For students who have chosen the project as their exam modality, we strongly recommend attending the lecture, as we will explain the project structure, requirements, and the first task.

Lorenzo

[17-09-2026] Introduction Python Notebook

Hi everyone, I have uploaded a notebook on Didawiki covering the basics of Python for those who are not familiar with the programming language.

Lorenzo

[15-09-2026] Exam Modality and Project Groups

Hi everyone, I have created a shared Google Sheet to collect information about your exam modality and, for students choosing the Project, to organize the project groups.

🔗 Google Sheet: see it in the Teams Channel of the course

⚠️ All students must fill in the Google Sheet, regardless of whether they choose the Project or the Written Exam.

Please fill in the following fields:

• ID: already pre-filled. Do not modify it.
• Surname, Name, Student ID, Email: enter your personal information.
• Curriculum: select your curriculum from the available options.
• Exam's modality: select one of the two available options:
• * Project
• * Written exam
• Group ID: fill in this field only if you choose the Project. Groups must consist of 3 students. All members of the same group must enter the same numerical Group ID. When creating a new group, use the next available number (e.g., if the last existing Group ID is 4, the new group should use 5).
• Note: optional; use it only if you need to communicate additional information.

📅 Deadline: September 29 By this date, all students must have completed the Google Sheet and selected their exam modality. Students choosing the Project must also have formed a group of 3 students and entered the corresponding Group ID. You are free to choose your group members. However, we encourage you to form groups with students from different curricula whenever possible, as different backgrounds can bring complementary knowledge and skills that can be useful when working on the project. Please make sure not to modify information entered by other students.

The Data Mining course tackles the analysis of large collections of data, and the extraction of information and patterns. It aims to explore core components of the Knowledge Discovery from Data (KDD) process, and focuses on:

• Data understanding
• Data cleaning, preparation, and transformation
• Data analysis: outlier detection and data representation
• Data clustering
• Anomaly detection
• Pattern extraction: itemset, rules, association rules, and sequential patterns
• Inference models: trees, and ensemble models
• Time Series
• Responsible data use: privacy and interpretability

Classes

Office hours - Ricevimento:

• Anna Monreale: TBD - Online using Teams or in my Office (Appointment by email).
• Lorenzo Mannocci: TBD

A https://teams.microsoft.com/l/team/19%3ATCuLDK4v7mUu1glOnSMQpceEjW9UYlClGxEwmjWq8Xs1%40thread.tacv2/conversations?groupId=a23b366e-ec68-4738-9104-f2321fe4e8e1&tenantId=c7456b31-a220-47f5-be52-473828670aa1 will be used ONLY to post news, Q&A, and other stuff related to the course. The lectures will be only in presence and will NOT be live-streamed.

Books

Online tutorials

Slides

The slides used in the course will be inserted in the calendar after each class. Some are part of the slides provided by the textbook's authors Slides per "Introduction to Data Mining".

• Exercises on Clustering: ex._clustering.pdf
• Some text of past exams of a similar course: 2017-1-19.pdf, 2017-9-6.pdf, 2016-05-30-dm1-seconda.pdf, dm2_exam.2017.06.13_solutions.pdf, dm2_exam.2017.07.04_solutions.pdf, dm2_mid-term_exam.2017.06.06_solutions.pdf
• Some exercises (partially with solutions) on sequential patterns and time series can be found in the following texts of exams from the last years: dm2_exam.2015.04.13.results.pdf, dm2_exam.2016.04.4_sol.pdf, dm2_exam.2016.04.5_sol.pdf, dm2_exam.2016.06.20_sol.pdf, dm2_exam.2016.07.08_sol.pdf
• Some very old exercises (part of them with solutions) are available here, most of them in Italian, not all of them on topics covered in this year program: Verifica 2006, Verifica 2005 (con soluzioni), Verifica 2004, Verifica 5 giugno 2007, Verifica 26 giugno 2007, Verifica 24 luglio 2007 (e Soluzioni), Verifica 18 luglio 2008 - parte 1, Verifica 18 luglio 2008 - parte 2, Exam with solution 2010-06-01,Exam with solution 2010-06-22, Exam with solution 2010-09-09, Exam with solution 2010-07-13

The exam can be taken in one of two ways:

Project track:

• Project to be delivered after the end of the course and discussed during the oral exam. Note that the project score will be finalized with the project discussion.
• Oral exam

During the course, you will have some “Project presentation” sessions wherein you’ll briefly (~3 minutes) present your work, and receive feedback from the lecturers. These sessions do not contribute to your grade.

Written test track

• Written exam: to be delivered during the standard exam sessions and can include both theoretical questions and exercises.
• Oral exam

Note that a passing grade for the project/written exam is required to be admitted to the oral exam.

Project Guidelines:

Project and Deadlines

Information about the dataset to be analyzed and project description:

• Dataset: https://unipiit-my.sharepoint.com/:u:/g/personal/a052176_unipi_it/IQAQ934-q6C0SI994CaIq3eeAdxH-xQRPM4rQArDGA011Jg?e=lJtXAZ
• Project description (first part): dm_-_project_2026_published.pdf
• Project Question & Answers:https://docs.google.com/spreadsheets/d/1rYpTG-dHj8My3k-7kJGb94EiV_B-gNvWNN6EeCN8Bdw/edit?usp=sharing
• Deadline: 4 January 2027
• How to book for the exam colloquium? In https://esami.unipi.it/ you can find the dates for the exam: one for January and one for February. Each student must do the registration on one of the 2 dates. These are not the dates of the colloquium but we will use the list of registered students for organizing the exam dates. We will share with you a calendar for the oral exam.

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Data Mining (309AA) - 9 CFU A.Y. 2022/2023

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